Carola-Bibiane Schönlieb

436 papers A* 19A 4B 3C 2Misc 3Journal 355Unranked 46

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Approximation Theory for Lipschitz Continuous Transformers. CoRR Takashi Furuya, Davide Murari, Carola-Bibiane Schönlieb
2026	A*	`conf`	Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. AAAI Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2026	J	`jnl`	Brain foundation models with hypergraph dynamic adapter for brain disease analysis. Pattern Recognit. Zhongying Deng, Haoyu Wang, Ziyan Huang, Lipei Zhang, Angelica I. Avilés-Rivero, Chaoyu Liu, Junjun He, Zoe Kourtzi, Carola-Bibiane Schönlieb
2026	J	`jnl`	Building Privacy-and-Security-Focused Federated Learning Infrastructure for Global Multi-Centre Healthcare Research. CoRR Fan Zhang, Daniel Kreuter, Javier Fernández-Marqués, BloodCounts Consortium, Gregory Verghese, Bernard Butler, Nicholas D. Lane, Suthesh Sivapalaratnam, Joseph Taylor, Norbert C. J. de Wit, Nicholas S. Gleadall, Carola-Bibiane Schönlieb, Michael Roberts
2026	J	`jnl`	Diffeomorphism-Equivariant Neural Networks. CoRR Josephine Elisabeth Oettinger, Zakhar Shumaylov, Johannes Bostelmann, Jan Lellmann, Carola-Bibiane Schönlieb
2026	J	`jnl`	Hierarchical Multiscale Structure-Function Coupling for Brain Connectome Integration. CoRR Jianwei Chen, Zhengyang Miao, Wenjie Cai, Jiaxue Tang, Boxing Liu, Yunfan Zhang, Yuhang Yang, Hao Tang, Carola-Bibiane Schönlieb, Zaixu Cui, Du Lei, Shouliang Qi, Chao Li
2026	J	`jnl`	Mamba neural operator: Who wins? transformers vs. state-space models for PDEs. J. Comput. Phys. Chun-Wun Cheng, Jiahao Huang, Yi Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2026	J	`jnl`	ProSMA-UNet: Decoder Conditioning for Proximal-Sparse Skip Feature Selection. CoRR Chun-Wun Cheng, Yanqi Cheng, Peiyuan Jing, Guang Yang, Javier A. Montoya-Zegarra, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2026	J	`jnl`	SpectraKAN: Conditioning Spectral Operators. CoRR Chun-Wun Cheng, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2026	J	`jnl`	Towards Improved Sentence Representations using Token Graphs. CoRR Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Zorah Lähner, Moshe Eliasof
2026	J	`jnl`	Trajectory Stitching for Solving Inverse Problems with Flow-Based Models. CoRR Alexander Denker, Moshe Eliasof, Zeljko Kereta, Carola-Bibiane Schönlieb
2025	J	`jnl`	A sparse optimization approach to infinite infimal convolution regularization. Numerische Mathematik Kristian Bredies, Marcello Carioni, Martin Holler, Yury Korolev, Carola-Bibiane Schönlieb
2025	J	`jnl`	ADFound: A Foundation Model for Diagnosis and Prognosis of Alzheimer's Disease. IEEE J. Biomed. Health Informatics Guangqian Yang, Kangrui Du, Zhihan Yang, Ye Du, Eva Yi Wah Cheung, Yongping Zheng, Mo Yang, Zoe Kourtzi, Carola-Bibiane Schönlieb, Shujun Wang
2025	J	`jnl`	Approximation theory for 1-Lipschitz ResNets. CoRR Davide Murari, Takashi Furuya, Carola-Bibiane Schönlieb
2025	J	`jnl`	Artificial immunofluorescence in a flash: Rapid synthetic imaging from brightfield through residual diffusion. Neurocomputing Xiaodan Xing, Chunling Tang, Siofra Murdoch, Giorgos Papanastasiou, Yunzhe Guo, Xianglu Xiao, Jan Oscar Cross-Zamirski, Carola-Bibiane Schönlieb, Kristina Xiao Liang, Zhangming Niu, Evandro Fei Fang, Yinhai Wang, Guang Yang
2025	J	`jnl`	Brain Foundation Models with Hypergraph Dynamic Adapter for Brain Disease Analysis. CoRR Zhongying Deng, Haoyu Wang, Ziyan Huang, Lipei Zhang, Angelica I. Avilés-Rivero, Chaoyu Liu, Junjun He, Zoe Kourtzi, Carola-Bibiane Schönlieb
2025	J	`jnl`	Bridging Annotation Gaps: Transferring Labels to Align Object Detection Datasets. CoRR Mikhail Kennerley, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Robby T. Tan
2025	J	`jnl`	Conservation-preserved Fourier Neural Operator through Adaptive Correction. CoRR Chaoyu Liu, Yangming Li, Zhongying Deng, Chris J. Budd, Carola-Bibiane Schönlieb
2025	J	`jnl`	Contrastive Registration for Unsupervised Medical Image Segmentation. IEEE Trans. Neural Networks Learn. Syst. Lihao Liu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2025	J	`jnl`	Convergent Regularization in Inverse Problems and Linear Plug-and-Play Denoisers. Found. Comput. Math. Andreas Hauptmann, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Ferdia Sherry
2025	A*	`conf`	Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations. AAAI Yi Zhang, Chun-Wun Cheng, Junyi He, Zhihai He, Carola-Bibiane Schönlieb, Yuyan Chen, Angelica I. Avilés-Rivero
2025	J	`jnl`	DNA-Prior: Unsupervised Denoise Anything via Dual-Domain Prior. CoRR Yanqi Cheng, Chun-Wun Cheng, Jim Denholm, Thiago Lima, Javier A. Montoya-Zegarra, Richard Goodwin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	J	`jnl`	Data-driven approaches to inverse problems. CoRR Carola-Bibiane Schönlieb, Zakhar Shumaylov
2025	J	`jnl`	Deep Block Proximal Linearized Minimization Algorithm for Nonconvex Inverse Problems. SIAM J. Math. Data Sci. Chaoyan Huang, Zhongming Wu, Yanqi Cheng, Tieyong Zeng, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	J	`jnl`	Deep Spectral Prior. CoRR Yanqi Cheng, Tieyong Zeng, Pietro Lio, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	A*	`conf`	DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations. CVPR Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro, Chaim Baskin, Moshe Eliasof
2025	J	`jnl`	DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations. CoRR Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro, Chaim Baskin, Moshe Eliasof
2025	—	`conf`	Enhanced Denoising and Convergent Regularisation Using Tweedie Scaling. SSVM (1) Naïl Khelifa, Carola-Bibiane Schönlieb, Ferdia Sherry
2025	J	`jnl`	Enhanced Denoising and Convergent Regularisation Using Tweedie Scaling. CoRR Naïl Khelifa, Ferdia Sherry, Carola-Bibiane Schönlieb
2025	J	`jnl`	Enhancing Fourier Neural Operators with Local Spatial Features. CoRR Chaoyu Liu, Davide Murari, Chris J. Budd, Lihao Liu, Carola-Bibiane Schönlieb
2025	J	`jnl`	Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba. Medical Image Anal. Jiahao Huang, Liutao Yang, Fanwen Wang, Yinzhe Wu, Yang Nan, Weiwen Wu, Chengyan Wang, Kuangyu Shi, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang
2025	A*	`conf`	Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement. ICLR Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann
2025	J	`jnl`	FLASH: Flexible Learning of Adaptive Sampling from History in Temporal Graph Neural Networks. CoRR Or Feldman, Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Chaim Baskin, Moshe Eliasof
2025	A*	`conf`	G-Adaptivity: optimised graph-based mesh relocation for finite element methods. ICML James Rowbottom, Georg Maierhofer, Teo Deveney, Eike Hermann Müller, Alberto Paganini, Katharina Schratz, Pietro Lio, Carola-Bibiane Schönlieb, Chris J. Budd
2025	J	`jnl`	GRAMA: Adaptive Graph Autoregressive Moving Average Models. CoRR Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2025	J	`jnl`	Generalized Lie Symmetries in Physics-Informed Neural Operators. CoRR Amy Xiang Wang, Zakhar Shumaylov, Peter Zaika, Ferdia Sherry, Carola-Bibiane Schönlieb
2025	J	`jnl`	Generative Unordered Flow for Set-Structured Data Generation. CoRR Yangming Li, Carola-Bibiane Schönlieb
2025	J	`jnl`	GeoSplat: A Deep Dive into Geometry-Constrained Gaussian Splatting. CoRR Yangming Li, Chaoyu Liu, Lihao Liu, Simon Masnou, Carola-Bibiane Schönlieb
2025	A*	`conf`	Graph Adaptive Autoregressive Moving Average Models. ICML Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2025	J	`jnl`	Graph Neural Regularizers for PDE Inverse Problems. CoRR William Lauga, James Rowbottom, Alexander Denker, Zeljko Kereta, Moshe Eliasof, Carola-Bibiane Schönlieb
2025	J	`jnl`	HypeR Adaptivity: Joint CoRR Niccolò Grillo, James Rowbottom, Pietro Liò, Carola-Bibiane Schönlieb, Stefania Fresca
2025	—	`conf`	Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation. MICCAI (11) Chun-Wun Cheng, Yining Zhao, Yanqi Cheng, Javier A. Montoya-Zegarra, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	J	`jnl`	Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation. CoRR Chun-Wun Cheng, Yining Zhao, Yanqi Cheng, Javier Montoya, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	J	`jnl`	Inverse Evolution Data Augmentation for Neural PDE Solvers. CoRR Chaoyu Liu, Chris J. Budd, Carola-Bibiane Schönlieb
2025	J	`jnl`	Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation. SIAM J. Math. Data Sci. Chaoyu Liu, Zhonghua Qiao, Chao Li, Carola-Bibiane Schönlieb
2025	Misc	`conf`	Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems. ICASSP Junqi Tang, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2025	J	`jnl`	LamiGauss: Pitching Radiative Gaussian for Sparse-View X-ray Laminography Reconstruction. CoRR Chu Chen, Ander Biguri, Jean-Michel Morel, Raymond H. Chan, Carola-Bibiane Schönlieb, Jizhou Li
2025	J	`jnl`	Laplace Learning in Wasserstein Space. CoRR Mary Chriselda Antony Oliver, Michael Roberts, Carola-Bibiane Schönlieb, Matthew Thorpe
2025	J	`jnl`	Learning Regularization Functionals for Inverse Problems: A Comparative Study. CoRR Johannes Hertrich, Hok Shing Wong, Alexander Denker, Stanislas Ducotterd, Zhenghan Fang, Markus Haltmeier, Zeljko Kereta, Erich Kobler, Oscar Leong, Mohammad Sadegh Salehi, Carola-Bibiane Schönlieb, Johannes Schwab, Zakhar Shumaylov, Jeremias Sulam, German Shâma Wache, Martin Zach, Yasi Zhang, Matthias J. Ehrhardt, Sebastian Neumayer
2025	A*	`conf`	Learning Regularization for Graph Inverse Problems. AAAI Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber
2025	J	`jnl`	Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction. IEEE Trans. Instrum. Meas. Liutao Yang, Jiahao Huang, Yingying Fang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang
2025	J	`jnl`	Learning homeomorphic image registration via conformal-invariant hyperelastic regularisation. Medical Image Anal. Jing Zou, Noémie Debroux, Lihao Liu, Jing Qin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	A*	`conf`	Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. ICLR Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb
2025	J	`jnl`	Maximum entropy on the mean and the Cramér rate function in statistical estimation and inverse problems: properties, models, and algorithms. Math. Program. Yakov Vaisbourd, Rustum Choksi, Ariel Goodwin, Tim Hoheisel, Carola-Bibiane Schönlieb
2025	J	`jnl`	Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling. CoRR Andrea Ceni, Alessio Gravina, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb, Moshe Eliasof
2025	J	`jnl`	Motion Constrained Point Cloud Matching for Maritime Tracking. IEEE Access Nicholas Dalhaug, Martin Baerveldt, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Annette Stahl, Rudolf Mester, Edmund Førland Brekke
2025	J	`jnl`	Multi-Level Monte Carlo Training of Neural Operators. CoRR James Rowbottom, Stefania Fresca, Pietro Lio, Carola-Bibiane Schönlieb, Nicolas Boullé
2025	J	`jnl`	Nested Bregman Iterations for Decomposition Problems. SIAM J. Imaging Sci. Tobias Wolf, Derek Driggs, Kostas Papafitsoros, Elena Resmerita, Carola-Bibiane Schönlieb
2025	J	`jnl`	Neural Networks with Orthogonal Jacobian. CoRR Alex Massucco, Davide Murari, Carola-Bibiane Schönlieb
2025	J	`jnl`	Neural varifolds: an aggregate representation for quantifying the geometry of point clouds. Trans. Mach. Learn. Res. Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, Simon Masnou
2025	A*	`conf`	On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems. AAAI Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2025	J	`jnl`	On the Effectiveness of Random Weights in Graph Neural Networks. CoRR Thu Bui, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof
2025	J	`jnl`	On the caveats of AI autophagy. Nat. Mac. Intell. Xiaodan Xing, Fadong Shi, Jiahao Huang, Yinzhe Wu, Yang Nan, Sheng Zhang, Yingying Fang, Michael Roberts, Carola-Bibiane Schönlieb, Javier Del Ser, Guang Yang
2025	J	`jnl`	PDE Solvers Should Be Local: Fast, Stable Rollouts with Learned Local Stencils. CoRR Chun-Wun Cheng, Bin Dong, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	—	`conf`	Parameter Choices in Haarpsi for IQA with Medical Images. ISBI Clemens Karner, Janek Gröhl, Ian Selby, Judith Babar, Jake Beckford, Thomas R. Else, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, James H. F. Rudd, Carola-Bibiane Schönlieb, Jonathan R. Weir-McCall, Anna Breger
2025	J	`jnl`	PhotIQA: A photoacoustic image data set with image quality ratings. CoRR Anna Breger, Janek Gröhl, Clemens Karner, Thomas R. Else, Ian Selby, Jonathan R. Weir-McCall, Carola-Bibiane Schönlieb
2025	—	`conf`	Potential Contrast: Properties, Equivalences, and Generalization to Multiple Classes. EUSIPCO Wallace Peaslee, Anna Breger, Carola-Bibiane Schönlieb
2025	J	`jnl`	Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Linear Inverse Problems. J. Math. Imaging Vis. Junqi Tang, Guixian Xu, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2025	J	`jnl`	RSFR: A Coarse-to-Fine Reconstruction Framework for Diffusion Tensor Cardiac MRI with Semantic-Aware Refinement. CoRR Jiahao Huang, Fanwen Wang, Pedro F. Ferreira, Haosen Zhang, Yinzhe Wu, Zhifan Gao, Lei Zhu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Ramyah Rajakulasingam, Ranil De Silva, Dudley J. Pennell, Guang Yang, Sonia Nielles-Vallespin
2025	J	`jnl`	Real-time CBCT reconstructions using Krylov solvers in repeated scanning procedures. CoRR Fred Vickers Hastings, S. M. Ragib Shahriar Islam, Malena Sabaté Landman, Sepideh Hatamikia, Carola-Bibiane Schönlieb, Ander Biguri
2025	J	`jnl`	Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks. CoRR Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Kamyar Azizzadenesheli, Xiaowen Dong, Pierre Vandergheynst
2025	J	`jnl`	Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis. CoRR Xu Chen, Yuan Huang, Benn Jessney, Jason Sangha, Sophie Gu, Carola-Bibiane Schönlieb, Martin Bennett, Michael Roberts
2025	—	`ed.`	Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part I SSVM (1) Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb
2025	—	`ed.`	Scale Space and Variational Methods in Computer Vision - 10th International Conference, SSVM 2025, Dartington, UK, May 18-22, 2025, Proceedings, Part II SSVM (2) Tatiana A. Bubba, Romina Gaburro, Silvia Gazzola, Kostas Papafitsoros, Marcelo Pereyra, Carola-Bibiane Schönlieb
2025	A*	`conf`	Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows. ICML Willem Diepeveen, Georgios Batzolis, Zakhar Shumaylov, Carola-Bibiane Schönlieb
2025	J	`jnl`	Smooth Model Compression without Fine-Tuning. CoRR Christina Runkel, Natacha Kuete Meli, Jovita Lukasik, Ander Biguri, Carola-Bibiane Schönlieb, Michael Möller
2025	—	`conf`	Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising. SSVM (2) Junqi Tang, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb
2025	J	`jnl`	SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events. CoRR Yichen Kelly Chen, Sören Dittmer, Kinga Bernatowicz, Josep Arús-Pous, Kamen Bliznashki, John A. D. Aston, James H. F. Rudd, Carola-Bibiane Schönlieb, James Jones, Michael Roberts
2025	J	`jnl`	TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows. CoRR Moshe Eliasof, Eldad Haber, Carola-Bibiane Schönlieb
2025	J	`jnl`	Towards Efficient Training of Graph Neural Networks: A Multiscale Approach. CoRR Eshed Gal, Moshe Eliasof, Carola-Bibiane Schönlieb, Eldad Haber, Eran Treister
2025	J	`jnl`	Towards Efficient Training of Graph Neural Networks: A Multiscale Approach. Trans. Mach. Learn. Res. Eshed Gal, Moshe Eliasof, Carola-Bibiane Schönlieb, Ivan I. Kyrchei, Eldad Haber, Eran Treister
2025	J	`jnl`	Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. Trans. Mach. Learn. Res. Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft
2025	J	`jnl`	Towards Invariance to Node Identifiers in Graph Neural Networks. CoRR Maya Bechler-Speicher, Moshe Eliasof, Carola-Bibiane Schönlieb, Ran Gilad-Bachrach, Amir Globerson
2025	J	`jnl`	TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation. IEEE Trans. Intell. Transp. Syst. Zhongying Deng, Yanqi Cheng, Lihao Liu, Shujun Wang, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	—	`conf`	Training Data Reconstruction: Privacy due to Uncertainty? CVPR Workshops Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller
2025	J	`jnl`	Training-Free Dual Hyperbolic Adapters for Better Cross-Modal Reasoning. CoRR Yi Zhang, Chun-Wun Cheng, Junyi He, Ke Yu, Yushun Tang, Carola-Bibiane Schönlieb, Zhihai He, Angelica I. Avilés-Rivero
2025	J	`jnl`	Vehicle detection from GSV imagery: Predicting travel behaviour for cycling and motorcycling using Computer Vision. CoRR Kyriaki Kokka, Rahul Goel, Ali Abbas, Kerry A. Nice, Luca Martial, S. M. Labib, Rihuan Ke, Carola-Bibiane Schönlieb, James Woodcock
2025	J	`jnl`	When is a System Discoverable from Data? Discovery Requires Chaos. CoRR Zakhar Shumaylov, Peter Zaika, Philipp Scholl, Gitta Kutyniok, Lior Horesh, Carola-Bibiane Schönlieb
2025	J	`jnl`	Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey. Trans. Mach. Learn. Res. Amer Essakine, Yanqi Cheng, Chun-Wun Cheng, Lipei Zhang, Zhongying Deng, Lei Zhu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	—	`conf`	A Study on the Adequacy of Common IQA Measures for Medical Images. MICAD Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Thomas R. Else, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
2024	J	`jnl`	A linear transportation Lp distance for pattern recognition. Pattern Recognit. Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis
2024	J	`jnl`	A study of why we need to reassess full reference image quality assessment with medical images. CoRR Anna Breger, Ander Biguri, Malena Sabaté Landman, Ian Selby, Nicole Amberg, Elisabeth Brunner, Janek Gröhl, Sepideh Hatamikia, Clemens Karner, Lipeng Ning, Sören Dittmer, Michael Roberts, AIX-COVNET Collaboration, Carola-Bibiane Schönlieb
2024	J	`jnl`	A study on the adequacy of common IQA measures for medical images. CoRR Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
2024	J	`jnl`	Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space. CoRR Yangming Li, Chieh-Hsin Lai, Carola-Bibiane Schönlieb, Yuki Mitsufuji, Stefano Ermon
2024	J	`jnl`	Benchmarking learned algorithms for computed tomography image reconstruction tasks. CoRR Maximilian B. Kiss, Ander Biguri, Zakhar Shumaylov, Ferdia Sherry, Kees Joost Batenburg, Carola-Bibiane Schönlieb, Felix Lucka
2024	J	`jnl`	Bilevel Hypergraph Networks for Multi-Modal Alzheimer's Diagnosis. CoRR Angelica I. Avilés-Rivero, Chun-Wun Cheng, Zhongying Deng, Zoe Kourtzi, Carola-Bibiane Schönlieb
2024	—	`conf`	Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation. MICCAI (12) Lipei Zhang, Yanqi Cheng, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation. CoRR Lipei Zhang, Yanqi Cheng, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. CoRR Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration. Trans. Mach. Learn. Res. Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Can generative AI replace immunofluorescent staining processes? A comparison study of synthetically generated cellpainting images from brightfield. Comput. Biol. Medicine Xiaodan Xing, Siofra Murdoch, Chunling Tang, Giorgos Papanastasiou, Jan Oscar Cross-Zamirski, Yunzhe Guo, Xianglu Xiao, Carola-Bibiane Schönlieb, Yinhai Wang, Guang Yang
2024	J	`jnl`	Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling. CoRR Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann
2024	—	`conf`	Continuous Learned Primal Dual. MLSP Christina Runkel, Ander Biguri, Carola-Bibiane Schönlieb
2024	J	`jnl`	Continuous Learned Primal Dual. CoRR Christina Runkel, Ander Biguri, Carola-Bibiane Schönlieb
2024	J	`jnl`	Continuous U-Net: Faster, Greater and Noiseless. Trans. Mach. Learn. Res. Chun-Wun Cheng, Christina Runkel, Lihao Liu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Contrastive Learning with Adaptive Neighborhoods for Brain Age Prediction on 3D Stiffness Maps. Trans. Mach. Learn. Res. Jakob Träuble, Lucy V. Hiscox, Curtis L. Johnson, Carola-Bibiane Schönlieb, Gabriele Kaminski Schierle, Angelica I. Avilés-Rivero
2024	J	`jnl`	Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps. CoRR Jakob Träuble, Lucy V. Hiscox, Curtis L. Johnson, Carola-Bibiane Schönlieb, Gabriele Kaminski Schierle, Angelica I. Avilés-Rivero
2024	J	`jnl`	Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations. CoRR Yi Zhang, Chun-Wun Cheng, Junyi He, Zhihai He, Carola-Bibiane Schönlieb, Yuyan Chen, Angelica I. Avilés-Rivero
2024	J	`jnl`	Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems. CoRR Chaoyan Huang, Zhongming Wu, Yanqi Cheng, Tieyong Zeng, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Deep Generative Classification of Blood Cell Morphology. CoRR Simon Deltadahl, Julian D. Gilbey, Christine van Laer, Nancy Boeckx, Mathie P. G. Leers, Tanya Freeman, Laura Aiken, Timothy Farren, Matthew Smith, Mohamad Zeina, BloodCounts Consortium, Concetta Piazzese, Joseph Taylor, Nicholas S. Gleadall, Carola-Bibiane Schönlieb, Suthesh Sivapalaratnam, Michael Roberts, Parashkev Nachev
2024	A*	`conf`	DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. NeurIPS Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof
2024	J	`jnl`	DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. CoRR Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof
2024	A*	`conf`	Diffusion Models Encode the Intrinsic Dimension of Data Manifolds. ICML Jan Stanczuk, Georgios Batzolis, Teo Deveney, Carola-Bibiane Schönlieb
2024	J	`jnl`	Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba. CoRR Jiahao Huang, Liutao Yang, Fanwen Wang, Yang Nan, Weiwen Wu, Chengyan Wang, Kuangyu Shi, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang
2024	J	`jnl`	FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimization. CoRR Fan Zhang, Carlos Esteve Yagüe, Sören Dittmer, Carola-Bibiane Schönlieb, Michael Roberts
2024	J	`jnl`	G-Adaptive mesh refinement - leveraging graph neural networks and differentiable finite element solvers. CoRR James Rowbottom, Georg Maierhofer, Teo Deveney, Katharina Schratz, Pietro Liò, Carola-Bibiane Schönlieb, Chris J. Budd
2024	A*	`conf`	GRANOLA: Adaptive Normalization for Graph Neural Networks. NeurIPS Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron
2024	J	`jnl`	GRANOLA: Adaptive Normalization for Graph Neural Networks. CoRR Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron
2024	A*	`conf`	HAMLET: Graph Transformer Neural Operator for Partial Differential Equations. ICML Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	HAMLET: Graph Transformer Neural Operator for Partial Differential Equations. CoRR Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Hamiltonian Matching for Symplectic Neural Integrators. CoRR Priscilla Canizares, Davide Murari, Carola-Bibiane Schönlieb, Ferdia Sherry, Zakhar Shumaylov
2024	J	`jnl`	Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI. Comput. Methods Programs Biomed. Simone Saitta, Marcello Carioni, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Alberto Redaelli
2024	J	`jnl`	LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification. IEEE Trans. Neural Networks Learn. Syst. Philip Sellars, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2024	J	`jnl`	Learned denoising with simulated and experimental low-dose CT data. CoRR Maximilian B. Kiss, Ander Biguri, Carola-Bibiane Schönlieb, Kees Joost Batenburg, Felix Lucka
2024	J	`jnl`	Learning Regularization for Graph Inverse Problems. CoRR Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber
2024	J	`jnl`	Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction. CoRR Liutao Yang, Jiahao Huang, Yingying Fang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang
2024	J	`jnl`	Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. CoRR Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb
2024	J	`jnl`	Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs. CoRR Chun-Wun Cheng, Jiahao Huang, Yi Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	MambaMIR: An Arbitrary-Masked Mamba for Joint Medical Image Reconstruction and Uncertainty Estimation. CoRR Jiahao Huang, Liutao Yang, Fanwen Wang, Yinzhe Wu, Yang Nan, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang
2024	J	`jnl`	Multi-objective Bayesian optimization with enhanced features for adaptively improved glioblastoma partitioning and survival prediction. Comput. Medical Imaging Graph. Yifan Li, Chao Li, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen
2024	J	`jnl`	NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems. SIAM J. Imaging Sci. Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang
2024	J	`jnl`	NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning. CoRR Yi Zhang, Chun-Wun Cheng, Ke Yu, Zhihai He, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Nested Bregman Iterations for Decomposition Problems. CoRR Tobias Wolf, Derek Driggs, Kostas Papafitsoros, Elena Resmerita, Carola-Bibiane Schönlieb
2024	J	`jnl`	Neural varifolds: an aggregate representation for quantifying the geometry of point clouds. CoRR Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, Simon Masnou
2024	J	`jnl`	NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning. Trans. Mach. Learn. Res. Zhongying Deng, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	A	`conf`	On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. AISTATS Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb
2024	J	`jnl`	On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. CoRR Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb
2024	J	`jnl`	On the Utilization of Unique Node Identifiers in Graph Neural Networks. CoRR Maya Bechler-Speicher, Moshe Eliasof, Carola-Bibiane Schönlieb, Ran Gilad-Bachrach, Amir Globerson
2024	J	`jnl`	Optimised ProPainter for Video Diminished Reality Inpainting. CoRR Pengze Li, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	—	`conf`	Optimised Propainter for Video Diminished Reality Inpainting. ISBI Pengze Li, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Parameter choices in HaarPSI for IQA with medical images. CoRR Clemens Karner, Janek Gröhl, Ian Selby, Judith Babar, Jake Beckford, Thomas R. Else, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, James H. F. Rudd, Carola-Bibiane Schönlieb, Jonathan R. Weir-McCall, Anna Breger
2024	J	`jnl`	Practical Acceleration of the Condat-Vũ Algorithm. SIAM J. Imaging Sci. Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang
2024	J	`jnl`	Provably Convergent Plug-and-Play Quasi-Newton Methods. SIAM J. Imaging Sci. Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Proximal Langevin Sampling with Inexact Proximal Mapping. SIAM J. Imaging Sci. Matthias J. Ehrhardt, Lorenz Kuger, Carola-Bibiane Schönlieb
2024	J	`jnl`	Publisher Correction: The curious case of the test set AUROC. Nat. Mac. Intell. Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb
2024	J	`jnl`	Pullback Flow Matching on Data Manifolds. CoRR Friso de Kruiff, Erik J. Bekkers, Ozan Öktem, Carola-Bibiane Schönlieb, Willem Diepeveen
2024	J	`jnl`	Recent methodological advances in federated learning for healthcare. Patterns Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie P. G. Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
2024	A	`conf`	Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach. ECAI Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb
2024	J	`jnl`	Score-based pullback Riemannian geometry. CoRR Willem Diepeveen, Georgios Batzolis, Zakhar Shumaylov, Carola-Bibiane Schönlieb
2024	J	`jnl`	Single-Shot Plug-and-Play Methods for Inverse Problems. Trans. Mach. Learn. Res. Yanqi Cheng, Lipei Zhang, Zhenda Shen, Shujun Wang, Lequan Yu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	—	`conf`	Spatiotemporal Graph Neural Network Modelling Perfusion MRI. MICCAI (2) Ruodan Yan, Carola-Bibiane Schönlieb, Chao Li
2024	J	`jnl`	Spatiotemporal Graph Neural Network Modelling Perfusion MRI. CoRR Ruodan Yan, Carola-Bibiane Schönlieb, Chao Li
2024	J	`jnl`	Stochastic Multiresolution Image Sketching for Inverse Imaging Problems. CoRR Alessandro Perelli, Carola-Bibiane Schönlieb, Matthias J. Ehrhardt
2024	J	`jnl`	Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes. J. Math. Imaging Vis. Antonin Chambolle, Claire Delplancke, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang
2024	J	`jnl`	Symplectic Neural Flows for Modeling and Discovery. CoRR Priscilla Canizares, Davide Murari, Carola-Bibiane Schönlieb, Ferdia Sherry, Zakhar Shumaylov
2024	J	`jnl`	TIGRE v3: Efficient and easy to use iterative computed tomographic reconstruction toolbox for real datasets. CoRR Ander Biguri, Tomoyuki Sadakane, Reuben Lindroos, Yi Liu, Malena Sabaté Landman, Yi Du, Manasavee Lohvithee, Stefanie Kaser, Sepideh Hatamikia, Robert Bryll, Emilien Valat, Sarinrat Wonglee, Thomas Blumensath, Carola-Bibiane Schönlieb
2024	J	`jnl`	Tackling Graph Oversquashing by Global and Local Non-Dissipativity. CoRR Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2024	J	`jnl`	The Missing U for Efficient Diffusion Models. Trans. Mach. Learn. Res. Sergio Calvo-Ordoñez, Chun-Wun Cheng, Jiahao Huang, Lipei Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	The curious case of the test set AUROC. Nat. Mac. Intell. Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb
2024	J	`jnl`	Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs. CoRR Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron
2024	J	`jnl`	Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. CoRR Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft
2024	A*	`conf`	TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. ACM Multimedia Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	Training Data Reconstruction: Privacy due to Uncertainty? CoRR Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller
2024	J	`jnl`	Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. CoRR Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. Trans. Mach. Learn. Res. Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	A*	`conf`	Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation. ICML Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2024	J	`jnl`	Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation. CoRR Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2024	J	`jnl`	When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI. CoRR Xiaodan Xing, Fadong Shi, Jiahao Huang, Yinzhe Wu, Yang Nan, Sheng Zhang, Yingying Fang, Mike Roberts, Carola-Bibiane Schönlieb, Javier Del Ser, Guang Yang
2024	J	`jnl`	Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey. CoRR Amer Essakine, Yanqi Cheng, Chun-Wun Cheng, Lipei Zhang, Zhongying Deng, Lei Zhu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2024	J	`jnl`	You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors. CoRR Yanqi Cheng, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	A Continuous-time Stochastic Gradient Descent Method for Continuous Data. J. Mach. Learn. Res. Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb
2023	J	`jnl`	Bang and the Artefacts are Gone! Rapid Artefact Removal and Tissue Segmentation in Haematoxylin and Eosin Stained Biopsies. CoRR B. A. Schreiber, J. Denholm, F. Jaeckle, M. J. Arends, Kim M. Branson, Carola-Bibiane Schönlieb, E. J. Soilleux
2023	J	`jnl`	Beyond U: Making Diffusion Models Faster & Lighter. CoRR Sergio Calvo-Ordoñez, Jiahao Huang, Lipei Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	—	`conf`	CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI? MICCAI (10) Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang
2023	J	`jnl`	CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI? CoRR Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang
2023	J	`jnl`	Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation. J. Digit. Imaging Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2023	J	`jnl`	Can Physics-Informed Neural Networks beat the Finite Element Method? CoRR Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz, Carola-Bibiane Schönlieb
2023	—	`conf`	Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels. ICCV (Workshops) Jan Oscar Cross-Zamirski, Praveen Anand, Guy B. Williams, Elizabeth Mouchet, Yinhai Wang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels. CoRR Jan Oscar Cross-Zamirski, Praveen Anand, Guy B. Williams, Elizabeth Mouchet, Yinhai Wang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Closing the ODE-SDE gap in score-based diffusion models through the Fokker-Planck equation. CoRR Teo Deveney, Jan Stanczuk, Lisa Maria Kreusser, Chris J. Budd, Carola-Bibiane Schönlieb
2023	J	`jnl`	CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting. CoRR Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen Yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Lihao Liu, Chenyang Hong, Angelica I. Avilés-Rivero, Ayushi Jain, Heeyoung Ahn, Yiyu Hong, Hussam Azzuni, Min Xu, Mohammad Yaqub, Marie-Claire Blache, Benoît Piégu, Bertrand Vernay, Tim Scherr, Moritz Böhland, Katharina Löffler, Jiachen Li, Weiqin Ying, Chixin Wang, Dagmar Kainmueller, Carola-Bibiane Schönlieb, Shuolin Liu, Dhairya Talsania, Yughender Meda, Prakash Mishra, Muhammad Ridzuan, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Banban Huang, Hsiang-Chin Chien, Ching-Ping Wang, Chia-Yen Lee, Hong-Kun Lin, Zaiyi Liu, Xipeng Pan, Chu Han, Jijun Cheng, Muhammad Dawood, Srijay Deshpande, Raja Muhammad Saad Bashir, Adam Shephard, Pedro Costa, João D. Nunes, Aurélio Campilho, Jaime S. Cardoso, Hrishikesh P. S, Densen Puthussery, Devika R. G, Jiji C V, Ye Zhang, Zijie Fang, Zhifan Lin, Yongbing Zhang, Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Thi Tuong Vi Vo, Soo-Hyung Kim, Taebum Lee, Satoshi Kondo, Satoshi Kasai, Pranay Dumbhare, Vedant Phuse, Yash Dubey, Ankush Jamthikar, Trinh Thi Le Vuong, Jin Tae Kwak, Dorsa Ziaei, Hyun Jung, Tianyi Miao, David R. J. Snead, Shan-E-Ahmed Raza, Fayyaz Minhas, Nasir M. Rajpoot
2023	J	`jnl`	Continuous U-Net: Faster, Greater and Noiseless. CoRR Chun-Wun Cheng, Christina Runkel, Lihao Liu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks. CoRR Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb
2023	J	`jnl`	Convergent regularization in inverse problems and linear plug-and-play denoisers. CoRR Andreas Hauptmann, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Ferdia Sherry
2023	J	`jnl`	Data-Driven Mirror Descent with Input-Convex Neural Networks. SIAM J. Math. Data Sci. Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study. CoRR Jiahao Huang, Pedro F. Ferreira, Lichao Wang, Yinzhe Wu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Ramyah Rajakulasingam, Ranil De Silva, Dudley J. Pennell, Sonia Nielles-Vallespin, Guang Yang
2023	J	`jnl`	Designing Stable Neural Networks using Convex Analysis and ODEs. CoRR Ferdia Sherry, Elena Celledoni, Matthias J. Ehrhardt, Davide Murari, Brynjulf Owren, Carola-Bibiane Schönlieb
2023	—	`conf`	DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification. MICCAI (6) Yijun Yang, Huazhu Fu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Lei Zhu
2023	J	`jnl`	DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification. CoRR Yijun Yang, Huazhu Fu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Lei Zhu
2023	J	`jnl`	Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data. CoRR Daniel Kreuter, Samuel Tull, Julian D. Gilbey, Jacobus Preller, BloodCounts Consortium, John A. D. Aston, James H. F. Rudd, Suthesh Sivapalaratnam, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
2023	J	`jnl`	Dynamical Systems-Based Neural Networks. SIAM J. Sci. Comput. Elena Celledoni, Davide Murari, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry
2023	—	`conf`	Expectation-Maximization Regularised Deep Learning for Tumour Segmentation. ISBI Chao Li, Wenjian Huang, Xi Chen, Yiran Wei, Lipei Zhang, Jianguo Zhang, Stephen J. Price, Carola-Bibiane Schönlieb
2023	—	`conf`	G-CNN: Adaptive Geometric Convolutional Neural Networks for MRI-Based Skull Stripping. CMMCA@MICCAI Yifan Li, Chao Li, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen
2023	J	`jnl`	Guest Editorial Special Issue on Geometric Deep Learning in Medical Imaging. IEEE Trans. Medical Imaging Huazhu Fu, Yitian Zhao, Pew-Thian Yap, Carola-Bibiane Schönlieb, Alejandro F. Frangi
2023	J	`jnl`	HGIB: Prognosis for Alzheimer's Disease via Hypergraph Information Bottleneck. CoRR Shujun Wang, Angelica I. Avilés-Rivero, Zoe Kourtzi, Carola-Bibiane Schönlieb
2023	J	`jnl`	Hidden Knowledge: Mathematical Methods for the Extraction of the Fingerprint of Medieval Paper from Digital Images. CoRR Tamara G. Grossmann, Carola-Bibiane Schönlieb, Orietta Da Rold
2023	J	`jnl`	Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation. CoRR Jing Zou, Noémie Debroux, Lihao Liu, Jing Qin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning. IEEE Signal Process. Mag. Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry, Julián Tachella
2023	J	`jnl`	Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI. CoRR Simone Saitta, Marcello Carioni, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Alberto Redaelli
2023	J	`jnl`	Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks. CoRR Chaoyu Liu, Zhonghua Qiao, Chao Li, Carola-Bibiane Schönlieb
2023	J	`jnl`	Joint Reconstruction-Segmentation on Graphs. SIAM J. Imaging Sci. Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto, Carola-Bibiane Schönlieb
2023	J	`jnl`	Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications. IEEE Signal Process. Mag. Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
2023	—	`conf`	Learning Posterior Distributions in Underdetermined Inverse Problems. SSVM Christina Runkel, Michael Möller, Carola-Bibiane Schönlieb, Christian Etmann
2023	J	`jnl`	MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening. CoRR Yijun Yang, Shujun Wang, Lihao Liu, Sarah Hickman, Fiona J. Gilbert, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	Multi-Modal Learning for Predicting the Genotype of Glioma. IEEE Trans. Medical Imaging Yiran Wei, Xi Chen, Lei Zhu, Lipei Zhang, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li
2023	J	`jnl`	NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems. CoRR Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang
2023	J	`jnl`	Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2023	—	`conf`	Predicting Conversion of Mild Cognitive Impairment to Alzheimer's Disease by Modelling Healthy Ageing Trajectories. ISBI Yiran Wei, Xi Chen, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li
2023	J	`jnl`	Provably Convergent Data-Driven Convex-Nonconvex Regularization. CoRR Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2023	J	`jnl`	Provably Convergent Plug-and-Play Quasi-Newton Methods. CoRR Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Proximal Langevin Sampling With Inexact Proximal Mapping. CoRR Matthias J. Ehrhardt, Lorenz Kuger, Carola-Bibiane Schönlieb
2023	J	`jnl`	Recent Methodological Advances in Federated Learning for Healthcare. CoRR Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, BloodCounts Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
2023	J	`jnl`	Regularizing Orientation Estimation in Cryogenic Electron Microscopy Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds. SIAM J. Imaging Sci. Willem Diepeveen, Jan Lellmann, Ozan Öktem, Carola-Bibiane Schönlieb
2023	J	`jnl`	Reinterpreting survival analysis in the universal approximator age. CoRR Sören Dittmer, Michael Roberts, Jacobus Preller, AIX-COVNET Collaboration, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2023	J	`jnl`	Riemannian geometry for efficient analysis of protein dynamics data. CoRR Willem Diepeveen, Carlos Esteve Yagüe, Jan Lellmann, Ozan Öktem, Carola-Bibiane Schönlieb
2023	Misc	`conf`	Robust Data-Driven Accelerated Mirror Descent. ICASSP Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Andreas Hauptmann, Carola-Bibiane Schönlieb
2023	J	`jnl`	S $^3$ Net: Self-Supervised Self-Ensembling Network for Semi-Supervised RGB-D Salient Object Detection. IEEE Trans. Multim. Lei Zhu, Xiaoqiang Wang, Ping Li, Xin Yang, Qing Zhang, Weiming Wang, Carola-Bibiane Schönlieb, C. L. Philip Chen
2023	A*	`conf`	SCOTCH and SODA: A Transformer Video Shadow Detection Framework. CVPR Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	Single-Shot Plug-and-Play Methods for Inverse Problems. CoRR Yanqi Cheng, Lipei Zhang, Zhenda Shen, Shujun Wang, Lequan Yu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations. CoRR Zhenda Shen, Yanqi Cheng, Raymond H. Chan, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	The curious case of the test set AUROC. CoRR Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb
2023	J	`jnl`	Traffic Video Object Detection using Motion Prior. CoRR Lihao Liu, Yanqi Cheng, Dongdong Chen, Jing He, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. CoRR Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2023	J	`jnl`	Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior. CoRR Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb
2023	J	`jnl`	ViGU: Vision GNN U-Net for Fast MRI. CoRR Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang
2023	—	`conf`	ViGU: Vision GNN U-Net for fast MRI. ISBI Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang
2023	—	`conf`	Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition Through the Lens of Robustness. TML4H Yanqi Cheng, Lihao Liu, Shujun Wang, Yueming Jin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	J	`jnl`	A Geometric Integration Approach to Nonsmooth, Nonconvex Optimisation. Found. Comput. Math. Erlend Skaldehaug Riis, Matthias J. Ehrhardt, G. R. W. Quispel, Carola-Bibiane Schönlieb
2022	J	`jnl`	A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation. IEEE Trans. Image Process. Rihuan Ke, Angelica I. Avilés-Rivero, Saurabh Pandey, Saikumar Reddy, Carola-Bibiane Schönlieb
2022	J	`jnl`	AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. Proc. IEEE Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Ge Wang, Daniel Rueckert, David N. Firmin, Guang Yang
2022	J	`jnl`	Accelerating Deep Unrolling Networks via Dimensionality Reduction. CoRR Junqi Tang, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2022	J	`jnl`	Accelerating variance-reduced stochastic gradient methods. Math. Program. Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb
2022	J	`jnl`	Beyond fine-tuning: Classifying high resolution mammograms using function-preserving transformations. Medical Image Anal. Tao Wei, Angelica I. Avilés-Rivero, Shuo Wang, Yuan Huang, Fiona J. Gilbert, Carola-Bibiane Schönlieb, Chang Wen Chen
2022	J	`jnl`	Classification of datasets with imputed missing values: does imputation quality matter? CoRR Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb
2022	—	`conf`	Collaborative Learning of Images and Geometrics for Predicting Isocitrate Dehydrogenase Status of Glioma. ISBI Yiran Wei, Chao Li, Xi Chen, Carola-Bibiane Schönlieb, Stephen J. Price
2022	J	`jnl`	Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma. CoRR Yiran Wei, Chao Li, Xi Chen, Carola-Bibiane Schönlieb, Stephen J. Price
2022	J	`jnl`	Dynamical systems' based neural networks. CoRR Elena Celledoni, Davide Murari, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry
2022	—	`conf`	Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation. ISBI Michael Yeung, Leonardo Rundo, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2022	J	`jnl`	GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays. Pattern Recognit. Angelica I. Avilés-Rivero, Philip Sellars, Carola-Bibiane Schönlieb, Nicolas Papadakis
2022	A	`conf`	HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation. WACV Hankui Peng, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2022	J	`jnl`	Image Reconstruction in Light-Sheet Microscopy: Spatially Varying Deconvolution and Mixed Noise. J. Math. Imaging Vis. Bogdan Toader, Jérôme Boulanger, Yury Korolev, Martin O. Lenz, James Manton, Carola-Bibiane Schönlieb, Leila Muresan
2022	J	`jnl`	Imaging with Equivariant Deep Learning. CoRR Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry, Julián Tachella
2022	J	`jnl`	Improving "Fast Iterative Shrinkage-Thresholding Algorithm": Faster, Smarter, and Greedier. SIAM J. Sci. Comput. Jingwei Liang, Tao Luo, Carola-Bibiane Schönlieb
2022	J	`jnl`	Joint reconstruction-segmentation on graphs. CoRR Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto, Carola-Bibiane Schönlieb
2022	J	`jnl`	Learned reconstruction with convergence guarantees. CoRR Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
2022	J	`jnl`	Maximum Entropy on the Mean and the Cramér Rate Function in Statistical Estimation and Inverse Problems: Properties, Models, and Algorithms. CoRR Yakov Vaisbourd, Rustum Choksi, Ariel Goodwin, Tim Hoheisel, Carola-Bibiane Schönlieb
2022	—	`ed.`	Medical Image Understanding and Analysis - 26th Annual Conference, MIUA 2022, Cambridge, UK, July 27-29, 2022, Proceedings MIUA Guang Yang, Angelica I. Avilés-Rivero, Michael Roberts, Carola-Bibiane Schönlieb
2022	J	`jnl`	Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification. CoRR Angelica I. Avilés-Rivero, Christina Runkel, Nicolas Papadakis, Zoe Kourtzi, Carola-Bibiane Schönlieb
2022	—	`conf`	Multi-modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification. MICCAI (3) Angelica I. Avilés-Rivero, Christina Runkel, Nicolas Papadakis, Zoe Kourtzi, Carola-Bibiane Schönlieb
2022	J	`jnl`	Multi-modal learning for predicting the genotype of glioma. CoRR Yiran Wei, Xi Chen, Lei Zhu, Lipei Zhang, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li
2022	—	`conf`	Multi-task Learning-Driven Volume and Slice Level Contrastive Learning for 3D Medical Image Classification. CMMCA@MICCAI Jiayuan Zhu, Shujun Wang, Jinzheng He, Carola-Bibiane Schönlieb, Lequan Yu
2022	J	`jnl`	Mutual Contrastive Learning to Disentangle Whole Slide Image Representations for Glioma Grading. CoRR Lipei Zhang, Yiran Wei, Ying Fu, Stephen J. Price, Carola-Bibiane Schönlieb, Chao Li
2022	A	`conf`	Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading. BMVC Lipei Zhang, Yiran Wei, Ying Fu, Stephen J. Price, Carola-Bibiane Schönlieb, Chao Li
2022	J	`jnl`	Navigating the challenges in creating complex data systems: a development philosophy. CoRR Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, AIX-COVNET Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2022	J	`jnl`	Non-Uniform Diffusion Models. CoRR Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
2022	J	`jnl`	NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning. CoRR Zhongying Deng, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	J	`jnl`	On Biased Stochastic Gradient Estimation. J. Mach. Learn. Res. Derek Driggs, Jingwei Liang, Carola-Bibiane Schönlieb
2022	J	`jnl`	On Krylov Methods for Large Scale CBCT Reconstruction. CoRR Malena Sabate Landman, Ander Biguri, Sepideh Hatamikia, Richard P. Boardman, John A. D. Aston, Carola-Bibiane Schönlieb
2022	J	`jnl`	PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation. CoRR Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	J	`jnl`	Predicting conversion of mild cognitive impairment to Alzheimer's disease. CoRR Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Chao Li
2022	—	`conf`	Rethinking Video Rain Streak Removal: A New Synthesis Model and a Deraining Network with Video Rain Prior. ECCV (19) Shuai Wang, Lei Zhu, Huazhu Fu, Jing Qin, Carola-Bibiane Schönlieb, Wei Feng, Song Wang
2022	J	`jnl`	SCOTCH and SODA: A Transformer Video Shadow Detection Framework. CoRR Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	J	`jnl`	Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels. CoRR Jan Oscar Cross-Zamirski, Guy B. Williams, Elizabeth Mouchet, Carola-Bibiane Schönlieb, Riku Turkki, Yinhai Wang
2022	J	`jnl`	Semi-Supervised Superpixel-Based Multi-Feature Graph Learning for Hyperspectral Image Data. IEEE Trans. Geosci. Remote. Sens. Madeleine S. Kotzagiannidis, Carola-Bibiane Schönlieb
2022	—	`conf`	Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting. MIUA Lihao Liu, Chenyang Hong, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2022	J	`jnl`	Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting. CoRR Lihao Liu, Chenyang Hong, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2022	J	`jnl`	Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning. CoRR Junqi Tang, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb
2022	Misc	`conf`	Stylegan-Induced Data-Driven Regularization for Inverse Problems. ICASSP Arthur Conmy, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2022	J	`jnl`	TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems. J. Mach. Learn. Res. Kaixuan Wei, Angelica I. Avilés-Rivero, Jingwei Liang, Ying Fu, Hua Huang, Carola-Bibiane Schönlieb
2022	J	`jnl`	TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation. CoRR Zhongying Deng, Yanqi Cheng, Lihao Liu, Shujun Wang, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	J	`jnl`	Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation. Comput. Medical Imaging Graph. Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2022	J	`jnl`	Unsupervised Clustering of Roman Potsherds via Variational Autoencoders. CoRR Simone Parisotto, Ninetta Leone, Carola-Bibiane Schönlieb, Alessandro Launaro
2022	J	`jnl`	Unsupervised Image Restoration Using Partially Linear Denoisers. IEEE Trans. Pattern Anal. Mach. Intell. Rihuan Ke, Carola-Bibiane Schönlieb
2022	J	`jnl`	Unsupervised Learning of the Total Variation Flow. CoRR Tamara G. Grossmann, Sören Dittmer, Yury Korolev, Carola-Bibiane Schönlieb
2022	J	`jnl`	Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness. CoRR Yanqi Cheng, Lihao Liu, Shujun Wang, Yueming Jin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	—	`conf`	You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration. WBIR Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2022	J	`jnl`	Your diffusion model secretly knows the dimension of the data manifold. CoRR Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb
2022	J	`jnl`	Γ-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation. CoRR Irene Fonseca, Lisa Maria Kreusser, Carola-Bibiane Schönlieb, Matthew Thorpe
2021	J	`jnl`	3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. Comput. Methods Programs Biomed. Maureen van Eijnatten, Leonardo Rundo, Kees Joost Batenburg, Felix Lucka, Emma Beddowes, Carlos Caldas, Ferdia A. Gallagher, Evis Sala, Carola-Bibiane Schönlieb, Ramona Woitek
2021	J	`jnl`	A Continuous-time Stochastic Gradient Descent Method for Continuous Data. CoRR Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb
2021	J	`jnl`	A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation. CoRR Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization. SIAM J. Imaging Sci. Derek Driggs, Junqi Tang, Jingwei Liang, Mike E. Davies, Carola-Bibiane Schönlieb
2021	J	`jnl`	AI-based Reconstruction for Fast MRI - A Systematic Review and Meta-analysis. CoRR Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Gerald Wang, Daniel Rueckert, David N. Firmin, Guang Yang
2021	—	`conf`	Adaptive Unsupervised Learning with Enhanced Feature Representation for Intra-tumor Partitioning and Survival Prediction for Glioblastoma. BrainLes@MICCAI (1) Yifan Li, Chao Li, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen
2021	J	`jnl`	Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma. CoRR Yifan Li, Chao Li, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen
2021	J	`jnl`	Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy. CoRR Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence. CoRR Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia
2021	—	`conf`	Adversarially Learned Iterative Reconstruction for Imaging Inverse Problems. SSVM Subhadip Mukherjee, Ozan Öktem, Carola-Bibiane Schönlieb
2021	J	`jnl`	Adversarially learned iterative reconstruction for imaging inverse problems. CoRR Subhadip Mukherjee, Ozan Öktem, Carola-Bibiane Schönlieb
2021	J	`jnl`	An end-to-end Optical Character Recognition approach for ultra-low-resolution printed text images. CoRR Julian D. Gilbey, Carola-Bibiane Schönlieb
2021	J	`jnl`	Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations. CoRR Tao Wei, Angelica I. Avilés-Rivero, Shuo Wang, Yuan Huang, Fiona J. Gilbert, Carola-Bibiane Schönlieb, Chang Wen Chen
2021	—	`conf`	BrainNetGAN: Data Augmentation of Brain Connectivity Using Generative Adversarial Network for Dementia Classification. DGM4MICCAI/DALI@MICCAI Chao Li, Yiran Wei, Xi Chen, Carola-Bibiane Schönlieb
2021	J	`jnl`	CAFLOW: Conditional Autoregressive Flows. CoRR Georgios Batzolis, Marcello Carioni, Christian Etmann, Soroosh Afyouni, Zoe Kourtzi, Carola-Bibiane Schönlieb
2021	J	`jnl`	Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation. CoRR Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2021	J	`jnl`	Choose Your Path Wisely: Gradient Descent in a Bregman Distance Framework. SIAM J. Imaging Sci. Martin Benning, Marta M. Betcke, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb
2021	J	`jnl`	Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. Michael Roberts, Derek Driggs, Matthew Thorpe, Julian D. Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Avilés-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, Effrossyni Gkrania-Klotsas, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb
2021	J	`jnl`	Compressed sensing plus motion (CS + M): A new perspective for improving undersampled MR image reconstruction. Medical Image Anal. Angelica I. Avilés-Rivero, Noémie Debroux, Guy B. Williams, Martin J. Graves, Carola-Bibiane Schönlieb
2021	J	`jnl`	Conditional Image Generation with Score-Based Diffusion Models. CoRR Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
2021	J	`jnl`	Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization. CoRR Christina Runkel, Christian Etmann, Michael Möller, Carola-Bibiane Schönlieb
2021	J	`jnl`	Dynamic spectral residual superpixels. Pattern Recognit. Jianchao Zhang, Angelica I. Avilés-Rivero, Daniel Heydecker, Xiaosheng Zhuang, Raymond H. Chan, Carola-Bibiane Schönlieb
2021	J	`jnl`	Efficient Global Optimization of Non-differentiable, Symmetric Objectives for Multi Camera Placement. CoRR Maria L. Hänel, Carola-Bibiane Schönlieb
2021	A*	`conf`	End-to-end reconstruction meets data-driven regularization for inverse problems. NeurIPS Subhadip Mukherjee, Marcello Carioni, Ozan Öktem, Carola-Bibiane Schönlieb
2021	J	`jnl`	End-to-end reconstruction meets data-driven regularization for inverse problems. CoRR Subhadip Mukherjee, Marcello Carioni, Ozan Öktem, Carola-Bibiane Schönlieb
2021	J	`jnl`	Equivariant neural networks for inverse problems. CoRR Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry
2021	J	`jnl`	Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma. CoRR Chao Li, Wenjian Huang, Xi Chen, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb
2021	J	`jnl`	Focal Attention Networks: optimising attention for biomedical image segmentation. CoRR Michael Yeung, Leonardo Rundo, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2021	J	`jnl`	Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy. Comput. Biol. Medicine Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	Image reconstruction in light-sheet microscopy: spatially varying deconvolution and mixed noise. CoRR Bogdan Toader, Jérôme Boulanger, Yury Korolev, Martin O. Lenz, James Manton, Carola-Bibiane Schönlieb, Leila Muresan
2021	J	`jnl`	Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation. CoRR Michael Yeung, Guang Yang, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification. CoRR Philip Sellars, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2021	J	`jnl`	Learning convex regularizers satisfying the variational source condition for inverse problems. CoRR Subhadip Mukherjee, Carola-Bibiane Schönlieb, Martin Burger
2021	J	`jnl`	Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks. IEEE Trans. Image Process. Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis, Mark Kirkland, Peter Schütz, Carola-Bibiane Schönlieb
2021	J	`jnl`	On Learned Operator Correction in Inverse Problems. SIAM J. Imaging Sci. Sebastian Lunz, Andreas Hauptmann, Tanja Tarvainen, Carola-Bibiane Schönlieb, Simon R. Arridge
2021	—	`conf`	Predicting Isocitrate Dehydrogenase Mutation Status in Glioma Using Structural Brain Networks and Graph Neural Networks. BrainLes@MICCAI (1) Yiran Wei, Yonghao Li, Xi Chen, Carola-Bibiane Schönlieb, Chao Li, Stephen J. Price
2021	J	`jnl`	Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks. CoRR Yiran Wei, Yonghao Li, Xi Chen, Carola-Bibiane Schönlieb, Chao Li, Stephen J. Price
2021	J	`jnl`	Radiological tumour classification across imaging modality and histology. Nat. Mach. Intell. Jia Wu, Chao Li, Michael Gensheimer, Sukhmani Padda, Fumi Kato, Hiroki Shirato, Yiran Wei, Carola-Bibiane Schönlieb, Stephen John Price, David A. Jaffray, John V. Heymach, Joel W. Neal, Billy W. Loo, Heather Wakelee, Maximilian Diehn, Ruijiang Li
2021	J	`jnl`	Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction. Medical Image Anal. Jiulong Liu, Angelica I. Avilés-Rivero, Hui Ji, Carola-Bibiane Schönlieb
2021	J	`jnl`	Semi-supervised Superpixel-based Multi-Feature Graph Learning for Hyperspectral Image Data. CoRR Madeleine Kotzagiannidis, Carola-Bibiane Schönlieb
2021	J	`jnl`	StyleGAN-induced data-driven regularization for inverse problems. CoRR Arthur Conmy, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2021	J	`jnl`	Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution. Medical Image Anal. Veronica Corona, Angelica I. Avilés-Rivero, Noémie Debroux, Carole Le Guyader, Carola-Bibiane Schönlieb
2021	J	`jnl`	Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance). CoRR Jan Stanczuk, Christian Etmann, Lisa Maria Kreusser, Carola-Bibiane Schönlieb
2020	J	`jnl`	3D Segmentation of Trees Through a Flexible Multiclass Graph Cut Algorithm. IEEE Trans. Geosci. Remote. Sens. Jonathan Williams, Carola-Bibiane Schönlieb, Tom Swinfield, Juheon Lee, Xiaohao Cai, Lan Qie, David A. Coomes
2020	J	`jnl`	3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. CoRR Maureen van Eijnatten, Leonardo Rundo, Kees Joost Batenburg, Felix Lucka, Emma Beddowes, Carlos Caldas, Ferdia A. Gallagher, Evis Sala, Carola-Bibiane Schönlieb, Ramona Woitek
2020	J	`jnl`	A Linear Transportation L CoRR Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis
2020	J	`jnl`	A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation. CoRR Rihuan Ke, Angelica I. Avilés-Rivero, Saurabh Pandey, Saikumar Reddy, Carola-Bibiane Schönlieb
2020	J	`jnl`	A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis. SIAM J. Imaging Sci. Noémie Debroux, John A. D. Aston, Fabien Bonardi, Alistair Forbes, Carole Le Guyader, Marina Romanchikova, Carola-Bibiane Schönlieb
2020	J	`jnl`	Analysis of Artifacts in Shell-Based Image Inpainting: Why They Occur and How to Eliminate Them. Found. Comput. Math. L. Robert Hocking, Thomas Holding, Carola-Bibiane Schönlieb
2020	J	`jnl`	Art Speaks Maths, Maths Speaks Art. CoRR Ninetta Leone, Simone Parisotto, Kasia Targonska-Hadzibabic, Spike Bucklow, Alessandro Launaro, Suzanne Reynolds, Carola-Bibiane Schönlieb
2020	J	`jnl`	Bregman Itoh-Abe Methods for Sparse Optimisation. J. Math. Imaging Vis. Martin Benning, Erlend Skaldehaug Riis, Carola-Bibiane Schönlieb
2020	J	`jnl`	Contrastive Registration for Unsupervised Medical Image Segmentation. CoRR Lihao Liu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2020	J	`jnl`	Deeply Learned Spectral Total Variation Decomposition. CoRR Tamara G. Grossmann, Yury Korolev, Guy Gilboa, Carola-Bibiane Schönlieb
2020	J	`jnl`	GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays. CoRR Angelica I. Avilés-Rivero, Philip Sellars, Carola-Bibiane Schönlieb, Nicolas Papadakis
2020	J	`jnl`	Ground Truth Free Denoising by Optimal Transport. CoRR Sören Dittmer, Carola-Bibiane Schönlieb, Peter Maass
2020	J	`jnl`	Higher-Order Total Directional Variation: Analysis. SIAM J. Imaging Sci. Simone Parisotto, Simon Masnou, Carola-Bibiane Schönlieb
2020	J	`jnl`	Higher-Order Total Directional Variation: Imaging Applications. SIAM J. Imaging Sci. Simone Parisotto, Jan Lellmann, Simon Masnou, Carola-Bibiane Schönlieb
2020	J	`jnl`	Learned convex regularizers for inverse problems. CoRR Subhadip Mukherjee, Sören Dittmer, Zakhar Shumaylov, Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb
2020	J	`jnl`	Learning the Sampling Pattern for MRI. IEEE Trans. Medical Imaging Ferdia Sherry, Martin Benning, Juan Carlos de los Reyes, Martin J. Graves, Georg Maierhofer, Guy B. Williams, Carola-Bibiane Schönlieb, Matthias Joachim Ehrhardt
2020	—	`conf`	Learning to Segment Microscopy Images with Lazy Labels. ECCV Workshops (1) Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis, Peter Schütz, Carola-Bibiane Schönlieb
2020	J	`jnl`	Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR Michael Roberts, Derek Driggs, Matthew Thorpe, Julian D. Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Avilés-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb
2020	J	`jnl`	Multi-task deep learning for image segmentation using recursive approximation tasks. CoRR Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis, Mark Kirkland, Peter Schütz, Carola-Bibiane Schönlieb
2020	J	`jnl`	On Learned Operator Correction. CoRR Sebastian Lunz, Andreas Hauptmann, Tanja Tarvainen, Carola-Bibiane Schönlieb, Simon R. Arridge
2020	J	`jnl`	Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding. CoRR Veronica Corona, Yehuda Dar, Carola-Bibiane Schönlieb
2020	J	`jnl`	SLIC-UAV: A Method for monitoring recovery in tropical restoration projects through identification of signature species using UAVs. CoRR Jonathan Williams, Carola-Bibiane Schönlieb, Tom Swinfield, Bambang Irawan, Eva Achmad, Muhammad Zudhi, Habibi, Elva Gemita, David A. Coomes
2020	J	`jnl`	Scanning electron diffraction tomography of strain. CoRR Robert Tovey, Duncan N. Johnstone, Sean M. Collins, William R. B. Lionheart, Paul A. Midgley, Martin Benning, Carola-Bibiane Schönlieb
2020	J	`jnl`	Structure preserving deep learning. CoRR Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann, Robert I. McLachlan, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry
2020	J	`jnl`	Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. Philip Sellars, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2020	J	`jnl`	TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems. CoRR Kaixuan Wei, Angelica I. Avilés-Rivero, Jingwei Liang, Ying Fu, Hua Huang, Carola-Bibiane Schönlieb
2020	A*	`conf`	Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems. ICML Kaixuan Wei, Angelica I. Avilés-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang
2020	J	`jnl`	Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems. CoRR Kaixuan Wei, Angelica I. Avilés-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang
2020	J	`jnl`	Two Cycle Learning: Clustering Based Regularisation for Deep Semi-Supervised Classification. CoRR Philip Sellars, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2020	J	`jnl`	Unsupervised Image Restoration Using Partially Linear Denoisers. CoRR Rihuan Ke, Carola-Bibiane Schönlieb
2020	J	`jnl`	Unsupervised clustering of Roman pottery profiles from their SSAE representation. CoRR Simone Parisotto, Alessandro Launaro, Ninetta Leone, Carola-Bibiane Schönlieb
2020	J	`jnl`	Variational Osmosis for Non-Linear Image Fusion. IEEE Trans. Image Process. Simone Parisotto, Luca Calatroni, Aurélie Bugeau, Nicolas Papadakis, Carola-Bibiane Schönlieb
2020	J	`jnl`	iUNets: Fully invertible U-Nets with Learnable Up- and Downsampling. CoRR Christian Etmann, Rihuan Ke, Carola-Bibiane Schönlieb
2020	—	`conf`	iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems. MLSP Christian Etmann, Rihuan Ke, Carola-Bibiane Schönlieb
2019	—	`conf`	A Total Variation Based Regularizer Promoting Piecewise-Lipschitz Reconstructions. SSVM Martin Burger, Yury Korolev, Carola-Bibiane Schönlieb, Christiane Stollenwerk
2019	J	`jnl`	A multi-task U-net for segmentation with lazy labels. CoRR Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis, Peter Schütz, Carola-Bibiane Schönlieb
2019	J	`jnl`	A total variation based regularizer promoting piecewise-Lipschitz reconstructions. CoRR Martin Burger, Yury Korolev, Carola-Bibiane Schönlieb, Christiane Stollenwerk
2019	J	`jnl`	Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian. CoRR Angelica I. Avilés-Rivero, Nicolas Papadakis, Ruoteng Li, Samar M. Alsaleh, Robby T. Tan, Carola-Bibiane Schönlieb
2019	J	`jnl`	Deep Reflection Prior. CoRR Qingnan Fan, Yingda Yin, Dongdong Chen, Yujie Wang, Angelica I. Avilés-Rivero, Ruoteng Li, Carola-Bibiane Schönlieb, Dani Lischinski, Baoquan Chen
2019	J	`jnl`	Deep learning as optimal control problems: models and numerical methods. CoRR Martin Benning, Elena Celledoni, Matthias J. Ehrhardt, Brynjulf Owren, Carola-Bibiane Schönlieb
2019	B	`conf`	Deep learning for inverse imaging problems: some recent approaches (Conference Presentation). Image Processing Carola-Bibiane Schönlieb
2019	J	`jnl`	Dynamic Spectral Residual Superpixels. CoRR Jianchao Zhang, Angelica I. Avilés-Rivero, Daniel Heydecker, Xiosheng Zhuang, Raymond H. Chan, Carola-Bibiane Schönlieb
2019	J	`jnl`	Equilibria of an anisotropic nonlocal interaction equation: Analysis and numerics. CoRR José A. Carrillo, Bertram Düring, Lisa Maria Kreusser, Carola-Bibiane Schönlieb
2019	—	`conf`	GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivative Induced Loss Functions. MICCAI (3) Pan Liu, Chao Li, Carola-Bibiane Schönlieb
2019	J	`jnl`	GraphX CoRR Angelica I. Avilés-Rivero, Nicolas Papadakis, Ruoteng Li, Philip Sellars, Qingnan Fan, Robby T. Tan, Carola-Bibiane Schönlieb
2019	—	`conf`	GraphX $$^\mathbf{\small NET } -$$ -Chest X-Ray Classification Under Extreme Minimal Supervision. MICCAI (6) Angelica I. Avilés-Rivero, Nicolas Papadakis, Ruoteng Li, Philip Sellars, Qingnan Fan, Robby T. Tan, Carola-Bibiane Schönlieb
2019	J	`jnl`	Learning the Sampling Pattern for MRI. CoRR Ferdia Sherry, Martin Benning, Juan Carlos de los Reyes, Martin J. Graves, Georg Maierhofer, Guy B. Williams, Carola-Bibiane Schönlieb, Matthias J. Ehrhardt
2019	J	`jnl`	Linkage Between Piecewise Constant Mumford-Shah Model and Rudin-Osher-Fatemi Model and Its Virtue in Image Segmentation. SIAM J. Sci. Comput. Xiaohao Cai, Raymond H. Chan, Carola-Bibiane Schönlieb, Gabriele Steidl, Tieyong Zeng
2019	J	`jnl`	Mirror, Mirror, on the Wall, Who's Got the Clearest Image of Them All? - A Tailored Approach to Single Image Reflection Removal. IEEE Trans. Image Process. Daniel Heydecker, Georg Maierhofer, Angelica I. Avilés-Rivero, Qingnan Fan, Dongdong Chen, Carola-Bibiane Schönlieb, Sabine Süsstrunk
2019	—	`conf`	Multi-tasking to Correct: Motion-Compensated MRI via Joint Reconstruction and Registration. SSVM Veronica Corona, Angelica I. Avilés-Rivero, Noémie Debroux, Martin J. Graves, Carole Le Guyader, Carola-Bibiane Schönlieb, Guy B. Williams
2019	J	`jnl`	On the Connection Between Adversarial Robustness and Saliency Map Interpretability. CoRR Christian Etmann, Sebastian Lunz, Peter Maass, Carola-Bibiane Schönlieb
2019	J	`jnl`	PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds. CoRR Oliver M. Crook, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis
2019	J	`jnl`	Rethinking Medical Image Reconstruction via Shape Prior, Going Deeper and Faster: Deep Joint Indirect Registration and Reconstruction. CoRR Jiulong Liu, Angelica I. Avilés-Rivero, Hui Ji, Carola-Bibiane Schönlieb
2019	C	`conf`	Semi-Supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification. IGARSS Philip Sellars, Angelica I. Avilés-Rivero, Nicolas Papadakis, David Coomes, Anita Faul, Carola-Bibiane Schönlieb
2019	J	`jnl`	Semi-supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification. CoRR Philip Sellars, Angelica I. Avilés-Rivero, Nicolas Papadakis, David Coomes, Anita Faul, Carola-Bibiane Schönlieb
2019	J	`jnl`	Solving inverse problems using data-driven models. Acta Numer. Simon R. Arridge, Peter Maass, Ozan Öktem, Carola-Bibiane Schönlieb
2019	J	`jnl`	Stability Analysis of Line Patterns of an Anisotropic Interaction Model. SIAM J. Appl. Dyn. Syst. José A. Carrillo, Bertram Düring, Lisa Maria Kreusser, Carola-Bibiane Schönlieb
2019	J	`jnl`	Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification. CoRR Philip Sellars, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb
2019	J	`jnl`	Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC). CoRR Jonathan V. Williams, Carola-Bibiane Schönlieb, Tom Swinfield, Juheon Lee, Xiaohao Cai, Lan Qie, David A. Coomes
2019	—	`conf`	Total Directional Variation for Video Denoising. SSVM Simone Parisotto, Carola-Bibiane Schönlieb
2019	J	`jnl`	Total Variation Regularisation with Spatially Variable Lipschitz Constraints. CoRR Martin Burger, Yury Korolev, Simone Parisotto, Carola-Bibiane Schönlieb
2019	J	`jnl`	Variational Multi-Task MRI Reconstruction: Joint Reconstruction, Registration and Super-Resolution. CoRR Veronica Corona, Angelica I. Avilés-Rivero, Noémie Debroux, Carole Le Guyader, Carola-Bibiane Schönlieb
2019	J	`jnl`	Variational Osmosis for Non-linear Image Fusion. CoRR Simone Parisotto, Luca Calatroni, Aurélie Bugeau, Nicolas Papadakis, Carola-Bibiane Schönlieb
2018	J	`jnl`	A Variational Model for Joint Motion Estimation and Image Reconstruction. SIAM J. Imaging Sci. Martin Burger, Hendrik Dirks, Carola-Bibiane Schönlieb
2018	J	`jnl`	Adversarial Regularizers in Inverse Problems. CoRR Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb
2018	—	`conf`	Faster FISTA. EUSIPCO Jingwei Liang, Carola-Bibiane Schönlieb
2018	J	`jnl`	Faster PET Reconstruction with Non-Smooth Priors by Randomization and Preconditioning. CoRR Matthias J. Ehrhardt, Pawel Markiewicz, Carola-Bibiane Schönlieb
2018	J	`jnl`	Linkage between Piecewise Constant Mumford-Shah model and ROF model and its virtue in image segmentation. CoRR Xiaohao Cai, Raymond H. Chan, Carola-Bibiane Schönlieb, Gabriele Steidl, Tieyong Zeng
2018	J	`jnl`	Mirror, Mirror, on the Wall, Who's Got the Clearest Image of Them All? - A Tailored Approach to Single Image Reflection Removal. CoRR Daniel Heydecker, Georg Maierhofer, Angelica I. Avilés-Rivero, Qingnan Fan, Carola-Bibiane Schönlieb, Sabine Süsstrunk
2018	J	`jnl`	Peekaboo - Where are the Objects? Structure Adjusting Superpixels. CoRR Georg Maierhofer, Daniel Heydecker, Angelica I. Avilés-Rivero, Samar M. Alsaleh, Carola-Bibiane Schönlieb
2018	B	`conf`	Peekaboo-Where are the Objects? Structure Adjusting Superpixels. ICIP Georg Maierhofer, Daniel Heydecker, Angelica I. Avilés-Rivero, Samar M. Alsaleh, Carola-Bibiane Schönlieb
2018	J	`jnl`	Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications. SIAM J. Optim. Antonin Chambolle, Matthias J. Ehrhardt, Peter Richtárik, Carola-Bibiane Schönlieb
2018	J	`jnl`	Task adapted reconstruction for inverse problems. CoRR Jonas Adler, Sebastian Lunz, Olivier Verdier, Carola-Bibiane Schönlieb, Ozan Öktem
2018	J	`jnl`	Unveiling the invisible - mathematical methods for restoring and interpreting illuminated manuscripts. CoRR Luca Calatroni, Marie d'Autume, Rob Hocking, Stella Panayotova, Simone Parisotto, Paola Ricciardi, Carola-Bibiane Schönlieb
2018	J	`jnl`	Variational Image Regularization with Euler's Elastica Using a Discrete Gradient Scheme. SIAM J. Imaging Sci. Torbjørn Ringholm, Jasmina Lazic, Carola-Bibiane Schönlieb
2017	J	`jnl`	A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery. CoRR Juheon Lee, David Coomes, Carola-Bibiane Schönlieb, Xiaohao Cai, Jan Lellmann, Michele Dalponte, Yadvinder Malhi, Nathalie Butt, Mike Morecroft
2017	J	`jnl`	Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models. J. Math. Imaging Vis. Juan Carlos de los Reyes, Carola-Bibiane Schönlieb, Tuomo Valkonen
2017	J	`jnl`	Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation. CoRR Leon Bungert, David A. Coomes, Matthias J. Ehrhardt, Jennifer Rasch, Rafael Reisenhofer, Carola-Bibiane Schönlieb
2017	J	`jnl`	Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images. J. Math. Imaging Vis. Luca Calatroni, Yves van Gennip, Carola-Bibiane Schönlieb, Hannah M. Rowland, Arjuna Flenner
2017	J	`jnl`	Guidefill: GPU Accelerated, Artist Guided Geometric Inpainting for 3D Conversion of Film. SIAM J. Imaging Sci. L. Robert Hocking, Russell MacKenzie, Carola-Bibiane Schönlieb
2017	J	`jnl`	Infimal Convolution of Data Discrepancies for Mixed Noise Removal. SIAM J. Imaging Sci. Luca Calatroni, Juan Carlos de los Reyes, Carola-Bibiane Schönlieb
2017	—	`conf`	Learning Filter Functions in Regularisers by Minimising Quotients. SSVM Martin Benning, Guy Gilboa, Joana Sarah Grah, Carola-Bibiane Schönlieb
2017	J	`jnl`	Learning to Diversify Deep Belief Networks for Hyperspectral Image Classification. IEEE Trans. Geosci. Remote. Sens. Ping Zhong, Zhiqiang Gong, Shutao Li, Carola-Bibiane Schönlieb
2017	—	`conf`	Nonlinear Spectral Image Fusion. SSVM Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa, Carola-Bibiane Schönlieb
2017	J	`jnl`	Nonlinear Spectral Image Fusion. CoRR Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger, Daniel Cremers, Guy Gilboa, Carola-Bibiane Schönlieb
2017	J	`jnl`	Numerical analysis of shell-based geometric image inpainting algorithms and their semi-implicit extension. CoRR L. Robert Hocking, Thomas Holding, Carola-Bibiane Schönlieb
2017	J	`jnl`	Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications. CoRR Antonin Chambolle, Matthias J. Ehrhardt, Peter Richtárik, Carola-Bibiane Schönlieb
2016	B	`conf`	A DBN-crf for spectral-spatial classification of hyperspectral data. ICPR Ping Zhong, Zhiqiang Gong, Carola-Bibiane Schönlieb
2016	J	`jnl`	A Variational Model for Joint Motion Estimation and Image Reconstruction. CoRR Martin Burger, Hendrik Dirks, Carola-Bibiane Schönlieb
2016	J	`jnl`	Graph clustering, variational image segmentation methods and Hough transform scale detection for object measurement in images. CoRR Luca Calatroni, Yves van Gennip, Carola-Bibiane Schönlieb, Hannah M. Rowland, Arjuna Flenner
2016	J	`jnl`	Guidefill: GPU Accelerated, Artist Guided Geometric Inpainting for 3D Conversion. CoRR L. Robert Hocking, Russell MacKenzie, Carola-Bibiane Schönlieb
2016	J	`jnl`	Individual Tree Species Classification From Airborne Multisensor Imagery Using Robust PCA. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Juheon Lee, Xiaohao Cai, Jan Lellmann, Michele Dalponte, Yadvinder Malhi, Nathalie Butt, Mike Morecroft, Carola-Bibiane Schönlieb, David A. Coomes
2016	J	`jnl`	Infimal Convolution Regularisation Functionals of BV and L J. Math. Imaging Vis. Martin Burger, Konstantinos Papafitsoros, Evangelos Papoutsellis, Carola-Bibiane Schönlieb
2016	—	`book`	Partial Differential Equation Methods for Image Inpainting. Carola-Bibiane Schönlieb
2015	J	`jnl`	Bilevel approaches for learning of variational imaging models. CoRR Luca Calatroni, Cao Chung, Juan Carlos de los Reyes, Carola-Bibiane Schönlieb, Tuomo Valkonen
2015	J	`jnl`	Bilevel parameter learning for higher-order total variation regularisation models. CoRR Juan Carlos de los Reyes, Carola-Bibiane Schönlieb, Tuomo Valkonen
2015	—	`conf`	Infimal Convolution Regularisation Functionals of BV and L System Modelling and Optimization Martin Burger, Konstantinos Papafitsoros, Evangelos Papoutsellis, Carola-Bibiane Schönlieb
2015	C	`conf`	Mapping individual trees from airborne multi-sensor imagery. IGARSS Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, David Coomes
2015	J	`jnl`	Nonparametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Wooded Landscapes. IEEE Trans. Geosci. Remote. Sens. Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, David Coomes
2015	—	`conf`	Preconditioned ADMM with Nonlinear Operator Constraint. System Modelling and Optimization Martin Benning, Florian Knoll, Carola-Bibiane Schönlieb, Tuomo Valkonen
2015	J	`jnl`	The structure of optimal parameters for image restoration problems. CoRR Juan Carlos de los Reyes, Carola-Bibiane Schönlieb, Tuomo Valkonen
2014	J	`jnl`	A Combined First and Second Order Variational Approach for Image Reconstruction. J. Math. Imaging Vis. Konstantinos Papafitsoros, Carola-Bibiane Schönlieb
2014	J	`jnl`	Imaging with Kantorovich-Rubinstein Discrepancy. SIAM J. Imaging Sci. Jan Lellmann, Dirk A. Lorenz, Carola-Bibiane Schönlieb, Tuomo Valkonen
2014	J	`jnl`	Non-parametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Forests. CoRR Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, David Coomes
2014	J	`jnl`	Variational Depth from Focus Reconstruction. CoRR Michael Möller, Martin Benning, Carola-Bibiane Schönlieb, Daniel Cremers
2013	—	`conf`	A Primal-Dual Approach for a Total Variation Wasserstein Flow. GSI Martin Benning, Luca Calatroni, Bertram Düring, Carola-Bibiane Schönlieb
2013	—	`conf`	Anisotropic Third-Order Regularization for Sparse Digital Elevation Models. SSVM Jan Lellmann, Jean-Michel Morel, Carola-Bibiane Schönlieb
2013	J	`jnl`	Bregmanized Domain Decomposition for Image Restoration. J. Sci. Comput. Andreas Langer, Stanley J. Osher, Carola-Bibiane Schönlieb
2013	J	`jnl`	Combined First and Second Order Total Variation Inpainting using Split Bregman. Image Process. Line Konstantinos Papafitsoros, Carola-Bibiane Schönlieb, Bati Sengul
2013	—	`conf`	Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints. System Modelling and Optimization Luca Calatroni, Juan Carlos de los Reyes, Carola-Bibiane Schönlieb
2012	J	`jnl`	Oriented diffusion filtering for enhancing low-quality fingerprint images. IET Biom. Carsten Gottschlich, Carola-Bibiane Schönlieb
2012	J	`jnl`	Wavelet Decomposition Method for L SIAM J. Imaging Sci. Massimo Fornasier, Yunho Kim, Andreas Langer, Carola-Bibiane Schönlieb
2010	J	`jnl`	A convergent overlapping domain decomposition method for total variation minimization. Numerische Mathematik Massimo Fornasier, Andreas Langer, Carola-Bibiane Schönlieb
2009	J	`jnl`	Cahn--Hilliard Inpainting and a Generalization for Grayvalue Images. SIAM J. Imaging Sci. Martin Burger, Lin He, Carola-Bibiane Schönlieb
2009	J	`jnl`	Subspace Correction Methods for Total Variation and SIAM J. Numer. Anal. Massimo Fornasier, Carola-Bibiane Schönlieb