Andreas Hauptmann

69 papers Misc 1Journal 63Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Graph Convolutional Networks Enable Fast Hemorrhagic Stroke Monitoring With Electrical Impedance Tomography. IEEE Trans. Biomed. Eng. Jussi Toivanen, Ville Kolehmainen, Antti Paldanius, Asko Hänninen, Andreas Hauptmann, Sarah Jane Hamilton
2026	J	`jnl`	Transformer Causality Regularization for Dynamic Inverse Problems. CoRR Gesa Sarnighausen, Anne Wald, Andreas Hauptmann
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	J	`jnl`	Digital twins enable full-reference quality assessment of photoacoustic image reconstructions. CoRR Janek Gröhl, Leonid Kunyansky, Jenni Poimala, Thomas R. Else, Francesca Di Cecio, Sarah E. Bohndiek, Ben T. Cox, Andreas Hauptmann
2025	J	`jnl`	Fast algorithms enabling optimization and deep learning for photoacoustic tomography in a circular detection geometry. CoRR Andreas Hauptmann, Leonid Kunyansky, Jenni Poimala
2025	J	`jnl`	Learned enclosure method for experimental EIT data. CoRR Sara Sippola, Siiri Rautio, Andreas Hauptmann, Takanori Ide, Samuli Siltanen
2025	J	`jnl`	Learned iterative networks: An operator learning perspective. CoRR Andreas Hauptmann, Ozan Öktem
2025	J	`jnl`	Regularization for time-dependent inverse problems: Geometry of Lebesgue-Bochner spaces and algorithms. CoRR Gesa Sarnighausen, Thorsten Hohage, Martin Burger, Andreas Hauptmann, Anne Wald
2024	—	`conf`	A Multi-Filter and Multi-Scale U-Net for Cone-Beam Computed Tomography with Hardware Constraints. ICASSP Workshops Andreas Hauptmann, Mustafa Al-Rubaye, Miika T. Nieminen, Mikael A. K. Brix
2024	J	`jnl`	Graph convolutional networks enable fast hemorrhagic stroke monitoring with electrical impedance tomography. CoRR Jussi Toivanen, Ville Kolehmainen, Antti Paldanius, Asko Hänninen, Andreas Hauptmann, Sarah Jane Hamilton
2024	J	`jnl`	Joint Activity Detection and Channel Estimation for Clustered Massive Machine Type Communications. IEEE Trans. Wirel. Commun. Leatile Marata, Onel Luis Alcaraz López, Andreas Hauptmann, Hamza Djelouat, Hirley Alves
2024	J	`jnl`	Self-Supervised Denoiser Framework. CoRR Emilien Valat, Andreas Hauptmann, Ozan Öktem
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`	Domain independent post-processing with graph U-nets: Applications to Electrical Impedance Tomographic Imaging. CoRR William Herzberg, Andreas Hauptmann, Sarah Jane Hamilton
2023	J	`jnl`	Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches. CoRR Derick Nganyu Tanyu, Jianfeng Ning, Andreas Hauptmann, Bangti Jin, Peter Maass
2023	J	`jnl`	Enhancement of instrumented ultrasonic tracking images using deep learning. Int. J. Comput. Assist. Radiol. Surg. Efthymios Maneas, Andreas Hauptmann, Erwin J. Alles, Wenfeng Xia, Sacha Noimark, Anna L. David, Simon R. Arridge, Adrien E. Desjardins
2023	J	`jnl`	Inverse Problems with Learned Forward Operators. CoRR Simon R. Arridge, Andreas Hauptmann, Yury Korolev
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	J	`jnl`	Model-based reconstructions for quantitative imaging in photoacoustic tomography. CoRR Andreas Hauptmann, Tanja Tarvainen
2023	J	`jnl`	Model-corrected learned primal-dual models for fast limited-view photoacoustic tomography. CoRR Andreas Hauptmann, Jenni Poimala
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`	Sequential Model Correction for Nonlinear Inverse Problems. SIAM J. Imaging Sci. Arttu Arjas, Mikko J. Sillanpää, Andreas Hauptmann
2023	J	`jnl`	Sequential model correction for nonlinear inverse problems. CoRR Arttu Arjas, Mikko J. Sillanpää, Andreas Hauptmann
2022	J	`jnl`	A Model-Based Iterative Learning Approach for Diffuse Optical Tomography. IEEE Trans. Medical Imaging Meghdoot Mozumder, Andreas Hauptmann, Ilkka Nissilä, Simon R. Arridge, Tanja Tarvainen
2022	J	`jnl`	An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. IEEE Trans. Computational Imaging Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maass, Bangti Jin
2022	J	`jnl`	Guest Editorial: MLSP 2020 Special Issue. J. Signal Process. Syst. Simo Särkkä, Lassi Roininen, Manon Kok, Roland Hostettler, Andreas Hauptmann
2022	J	`jnl`	Learned reconstruction with convergence guarantees. CoRR Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
2022	J	`jnl`	Reconstruction and segmentation from sparse sequential X-ray measurements of wood logs. CoRR Sebastian Springer, Aldo Glielmo, Angelina Senchukova, Tomi Kauppi, Jarkko Suuronen, Lassi Roininen, Heikki Haario, Andreas Hauptmann
2022	J	`jnl`	Sparsity promoting reconstructions via hierarchical prior models in diffuse optical tomography. CoRR Anssi Manninen, Meghdoot Mozumder, Tanja Tarvainen, Andreas Hauptmann
2022	J	`jnl`	Unsupervised denoising for sparse multi-spectral computed tomography. CoRR Satu I. Inkinen, Mikael A. K. Brix, Miika T. Nieminen, Simon R. Arridge, Andreas Hauptmann
2021	J	`jnl`	An Efficient Quasi-Newton Method for Nonlinear Inverse Problems via Learned Singular Values. IEEE Signal Process. Lett. Danny Smyl, Tyler N. Tallman, Dong Liu, Andreas Hauptmann
2021	J	`jnl`	Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems. CoRR William Herzberg, Daniel B. Rowe, Andreas Hauptmann, Sarah Jane Hamilton
2021	J	`jnl`	Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems. IEEE Trans. Computational Imaging William Herzberg, Daniel B. Rowe, Andreas Hauptmann, Sarah Jane Hamilton
2021	J	`jnl`	Is Deep Image Prior in Need of a Good Education? CoRR Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin
2021	J	`jnl`	Learning and correcting non-Gaussian model errors. J. Comput. Phys. Danny Smyl, Tyler N. Tallman, Jonathan A. Black, Andreas Hauptmann, Dong Liu
2021	J	`jnl`	Material Decomposition in Spectral CT Using Deep Learning: A Sim2Real Transfer Approach. IEEE Access Juan F. P. J. Abascal, Nicolas Ducros, Valeriya Pronina, Simon Rit, Pierre-Antoine Rodesch, Thomas Broussaud, Suzanne Bussod, Philippe C. Douek, Andreas Hauptmann, Simon R. Arridge, Françoise Peyrin
2021	J	`jnl`	Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data. CoRR Arttu Arjas, Erwin J. Alles, Efthymios Maneas, Simon R. Arridge, Adrien E. Desjardins, Mikko J. Sillanpää, Andreas Hauptmann
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	J	`jnl`	Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
2020	J	`jnl`	An efficient Quasi-Newton method for nonlinear inverse problems via learned singular values. CoRR Danny Smyl, Tyler N. Tallman, Dong Liu, Andreas Hauptmann
2020	—	`conf`	Blind Hierarchical Deconvolution. MLSP Arttu Arjas, Lassi Roininen, Mikko J. Sillanpää, Andreas Hauptmann
2020	J	`jnl`	Blind hierarchical deconvolution. CoRR Arttu Arjas, Lassi Roininen, Mikko J. Sillanpää, Andreas Hauptmann
2020	—	`conf`	Convolutional Neural Network for Material Decomposition in Spectral CT Scans. EUSIPCO Suzanne Bussod, Juan F. P. J. Abascal, Simon R. Arridge, Andreas Hauptmann, Christine Chappard, Nicolas Ducros, Françoise Peyrin
2020	J	`jnl`	Deep Learning in Photoacoustic Tomography: Current approaches and future directions. CoRR Andreas Hauptmann, Ben T. Cox
2020	J	`jnl`	Estimation of dynamic SNP-heritability with Bayesian Gaussian process models. Bioinform. Arttu Arjas, Andreas Hauptmann, Mikko J. Sillanpää
2020	J	`jnl`	Fusing electrical and elasticity imaging. CoRR Andreas Hauptmann, Danny Smyl
2020	J	`jnl`	Image reconstruction in dynamic inverse problems with temporal models. CoRR Andreas Hauptmann, Ozan Öktem, Carola Schönlieb
2020	J	`jnl`	Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems. CoRR Simon Robert Arridge, Pascal Fernsel, Andreas Hauptmann
2020	J	`jnl`	Learning and correcting non-Gaussian model errors. CoRR Danny Smyl, Tyler N. Tallman, Jonathan A. Black, Andreas Hauptmann, Dong Liu
2020	J	`jnl`	Machine Learning in Magnetic Resonance Imaging: Image Reconstruction. CoRR Javier Montalt-Tordera, Vivek Muthurangu, Andreas Hauptmann, Jennifer Anne Steeden
2020	—	`conf`	Material Decomposition Problem in Spectral CT: A Transfer Deep Learning Approach. ISBI Workshops Juan F. P. J. Abascal, Nicolas Ducros, Valeriya Pronina, Suzanne Bussod, Andreas Hauptmann, Simon R. Arridge, Philippe Douek, Françoise Peyrin
2020	J	`jnl`	Multi-Scale Learned Iterative Reconstruction. IEEE Trans. Computational Imaging Andreas Hauptmann, Jonas Adler, Simon R. Arridge, Ozan Öktem
2020	J	`jnl`	Networks for Nonlinear Diffusion Problems in Imaging. J. Math. Imaging Vis. Simon R. Arridge, Andreas Hauptmann
2020	J	`jnl`	On Learned Operator Correction. CoRR Sebastian Lunz, Andreas Hauptmann, Tanja Tarvainen, Carola-Bibiane Schönlieb, Simon R. Arridge
2020	J	`jnl`	On the unreasonable effectiveness of CNNs. CoRR Andreas Hauptmann, Jonas Adler
2020	J	`jnl`	Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
2020	J	`jnl`	Sequentially optimized projections in X-ray imaging. CoRR Martin Burger, Andreas Hauptmann, Tapio Helin, Nuutti Hyvönen, Juha-Pekka Puska
2019	J	`jnl`	Multi-Scale Learned Iterative Reconstruction. CoRR Andreas Hauptmann, Jonas Adler, Simon R. Arridge, Ozan Öktem
2019	J	`jnl`	Rapid Whole-Heart CMR with Single Volume Super-resolution. CoRR Jennifer Anne Steeden, Michael Quail, Alexander Gotschy, Andreas Hauptmann, Simon R. Arridge, Rodney Jones, Vivek Muthurangu
2018	—	`conf`	Approximate k-Space Models and Deep Learning for Fast Photoacoustic Reconstruction. MLMIR@MICCAI Andreas Hauptmann, Ben T. Cox, Felix Lucka, Nam Huynh, Marta M. Betcke, Paul C. Beard, Simon R. Arridge
2018	J	`jnl`	Approximate k-space models and Deep Learning for fast photoacoustic reconstruction. CoRR Andreas Hauptmann, Ben T. Cox, Felix Lucka, Nam Huynh, Marta M. Betcke, Paul C. Beard, Simon R. Arridge
2018	J	`jnl`	Beltrami-Net: Domain Independent Deep D-bar Learning for Absolute Imaging with Electrical Impedance Tomography (a-EIT). CoRR Sarah Jane Hamilton, Asko Hänninen, Andreas Hauptmann, Ville Kolehmainen
2018	J	`jnl`	Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With Deep Neural Networks. IEEE Trans. Medical Imaging Sarah Jane Hamilton, Andreas Hauptmann
2018	J	`jnl`	Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography. IEEE Trans. Medical Imaging Andreas Hauptmann, Felix Lucka, Marta M. Betcke, Nam Huynh, Jonas Adler, Ben T. Cox, Paul C. Beard, Sébastien Ourselin, Simon R. Arridge
2018	J	`jnl`	Networks for Nonlinear Diffusion Problems in Imaging. CoRR Simon R. Arridge, Andreas Hauptmann
2018	J	`jnl`	Real-time Cardiovascular MR with Spatio-temporal De-aliasing using Deep Learning - Proof of Concept in Congenital Heart Disease. CoRR Andreas Hauptmann, Simon R. Arridge, Felix Lucka, Vivek Muthurangu, Jennifer Anne Steeden
2018	J	`jnl`	Revealing cracks inside conductive bodies by electric surface measurements. CoRR Andreas Hauptmann, Masaru Ikehata, Hiromichi Itou, Samuli Siltanen
2017	J	`jnl`	Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep Neural Networks. CoRR Sarah Jane Hamilton, Andreas Hauptmann
2017	J	`jnl`	Model based learning for accelerated, limited-view 3D photoacoustic tomography. CoRR Andreas Hauptmann, Felix Lucka, Marta M. Betcke, Nam Huynh, Ben T. Cox, Paul C. Beard, Sébastien Ourselin, Simon R. Arridge