Peter Maass - RankMe

63 papers A* 1Misc 1Journal 54Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Medical Image Reconstruction. IEEE Trans. Medical Imaging Riccardo Barbano, Alexander Denker, Hyungjin Chung, Tae-Hoon Roh, Simon R. Arridge, Peter Maass, Bangti Jin, Jong Chul Ye
2024	J	`jnl`	Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data. CoRR Alexander Denker, Zeljko Kereta, Imraj RD Singh, Tom Freudenberg, Tobias Kluth, Peter Maass, Simon R. Arridge
2024	J	`jnl`	Enhancing the analysis of murine neonatal ultrasonic vocalizations: Development, evaluation, and application of different mathematical models. CoRR Rudolf Herdt, Louisa Kinzel, Johann Georg Maaß, Marvin Walther, Henning Fröhlich, Tim Schubert, Peter Maass, Christian Patrick Schaaf
2024	—	`conf`	Visualize and Paint GAN Activations. MLSP Rudolf Herdt, Peter Maass
2024	J	`jnl`	Visualize and Paint GAN Activations. CoRR Rudolf Herdt, Peter Maass
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`	Invertible residual networks in the context of regularization theory for linear inverse problems. CoRR Clemens Arndt, Alexander Denker, Sören Dittmer, Nick Heilenkötter, Meira Iske, Tobias Kluth, Peter Maass, Judith Nickel
2023	J	`jnl`	Model Stitching and Visualization How GAN Generators can Invert Networks in Real-Time. CoRR Rudolf Herdt, Maximilian Schmidt, Daniel Otero Baguer, Jean Le'Clerc Arrastia, Peter Maass
2023	J	`jnl`	Parameter Identification by Deep Learning of a Material Model for Granular Media. CoRR Derick Nganyu Tanyu, Isabel Michel, Andreas Rademacher, Jörg Kuhnert, Peter Maass
2023	—	`conf`	SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. MIDL Marco Nittscher, Michael Falk Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
2023	J	`jnl`	SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
2023	J	`jnl`	Score-Based Generative Models for PET Image Reconstruction. CoRR Imraj RD Singh, Alexander Denker, Riccardo Barbano, Zeljko Kereta, Bangti Jin, Kris Thielemans, Peter Maass, Simon R. Arridge
2023	J	`jnl`	Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems. CoRR Riccardo Barbano, Alexander Denker, Hyungjin Chung, Tae-Hoon Roh, Simon Arrdige, Peter Maass, Bangti Jin, Jong Chul Ye
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`	Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems. CoRR Derick Nganyu Tanyu, Jianfeng Ning, Tom Freudenberg, Nick Heilenkötter, Andreas Rademacher, Uwe Iben, Peter Maass
2022	J	`jnl`	PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization. CoRR Fabian Altekrüger, Alexander Denker, Paul Hagemann, Johannes Hertrich, Peter Maass, Gabriele Steidl
2022	J	`jnl`	SELTO: Sample-Efficient Learned Topology Optimization. CoRR Sören Dittmer, David Erzmann, Henrik Harms, Peter Maass
2022	J	`jnl`	StainCUT: Stain Normalization with Contrastive Learning. J. Imaging José Carlos Gutiérrez Menéndez, Daniel Otero Baguer, Peter Maass
2021	J	`jnl`	Conditional Invertible Neural Networks for Medical Imaging. J. Imaging Alexander Denker, Maximilian Schmidt, Johannes Leuschner, Peter Maass
2021	J	`jnl`	Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma. J. Imaging Jean Le'Clerc Arrastia, Nick Heilenkötter, Daniel Otero Baguer, Lena Hauberg-Lotte, Tobias Boskamp, Sonja Hetzer, Nicole Duschner, Jörg Schaller, Peter Maass
2021	J	`jnl`	Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications. J. Imaging Johannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, Vladyslav Andriiashen, Sophia Bethany Coban, Alexander Denker, Dominik F. Bauer, Amir Hadjifaradji, Kees Joost Batenburg, Peter Maass, Maureen van Eijnatten
2021	J	`jnl`	Regularized Orthogonal Nonnegative Matrix Factorization and K-means Clustering. CoRR Pascal Fernsel, Peter Maass
2020	—	`conf`	A Deep Prior Approach to Magnetic Particle Imaging. MLMIR@MICCAI Sören Dittmer, Tobias Kluth, Daniel Otero Baguer, Peter Maass
2020	J	`jnl`	Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset. CoRR Sören Dittmer, Tobias Kluth, Mads Thorstein Roar Henriksen, Peter Maass
2020	J	`jnl`	Error analysis for filtered back projection reconstructions in Besov spaces. CoRR Matthias Beckmann, Peter Maass, Judith Nickel
2020	J	`jnl`	Ground Truth Free Denoising by Optimal Transport. CoRR Sören Dittmer, Carola-Bibiane Schönlieb, Peter Maass
2020	J	`jnl`	Joint super-resolution image reconstruction and parameter identification in imaging operator: Analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging. CoRR Tobias Kluth, Christine Bathke, Ming Jiang, Peter Maass
2020	J	`jnl`	Regularization by Architecture: A Deep Prior Approach for Inverse Problems. J. Math. Imaging Vis. Sören Dittmer, Tobias Kluth, Peter Maass, Daniel Otero Baguer
2020	J	`jnl`	Singular Values for ReLU Layers. IEEE Trans. Neural Networks Learn. Syst. Sören Dittmer, Emily J. King, Peter Maass
2019	J	`jnl`	A Projectional Ansatz to Reconstruction. CoRR Sören Dittmer, Peter Maass
2019	J	`jnl`	Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data. CoRR Christian Etmann, Maximilian Schmidt, Jens Behrmann, Tobias Boskamp, Lena Hauberg-Lotte, Annette Peter, Rita Casadonte, Jörg Kriegsmann, Peter Maass
2019	—	`conf`	Joint Bi-Modal Image Reconstruction Of Dot And Xct With An Extended Mumford-Shah Functional. ISBI Di He, Ming Jiang, Alfred K. Louis, Peter Maass, Thomas Page
2019	A*	`conf`	On the Connection Between Adversarial Robustness and Saliency Map Interpretability. ICML Christian Etmann, Sebastian Lunz, Peter Maass, Carola Schönlieb
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`	Solving inverse problems using data-driven models. Acta Numer. Simon R. Arridge, Peter Maass, Ozan Öktem, Carola-Bibiane Schönlieb
2019	J	`jnl`	Supervised non-negative matrix factorization methods for MALDI imaging applications. Bioinform. Johannes Leuschner, Maximilian Schmidt, Pascal Fernsel, Delf Lachmund, Tobias Boskamp, Peter Maass
2018	J	`jnl`	A Survey on Surrogate Approaches to Non-negative Matrix Factorization. CoRR Pascal Fernsel, Peter Maass
2018	J	`jnl`	Regularization by architecture: A deep prior approach for inverse problems. CoRR Sören Dittmer, Tobias Kluth, Peter Maass, Daniel Otero Baguer
2018	J	`jnl`	Singular Values for ReLU Layers. CoRR Sören Dittmer, Emily J. King, Peter Maass
2017	J	`jnl`	Deep Learning for Tumor Classification in Imaging Mass Spectrometry. CoRR Jens Behrmann, Christian Etmann, Tobias Boskamp, Rita Casadonte, Jörg Kriegsmann, Peter Maass
2016	J	`jnl`	Descent gradient methods for nonsmooth minimization problems in ill-posed problems. J. Comput. Appl. Math. Pham Quy Muoi, Dinh Nho Hào, Peter Maass, Michael Pidcock
2014	Misc	`conf`	FPGA Acceleration for Simultaneous Medical Image Reconstruction and Segmentation. FCCM Peng Li, Thomas Page, Guojie Luo, Wentai Zhang, Pei Wang, Peng Zhang, Peter Maass, Ming Jiang, Jason Cong
2014	J	`jnl`	Numerical experiments with MALDI Imaging data. Adv. Comput. Math. Jan Hendrik Kobarg, Peter Maass, Janina Oetjen, Oren Tropp, Eyal Hirsch, Chen Sagiv, Mohammad Golbabaee, Pierre Vandergheynst
2014	J	`jnl`	Signal representation, uncertainty principles and localization measures. Adv. Comput. Math. Peter Maass, Chen Sagiv, Hans-Georg Stark, Bruno Torrésani
2012	—	`conf`	3D Visualisierung von Organismen. GI-Jahrestagung Herbert Thiele, Dennis Trede, Stefan Heldmann, Theodore Alexandrov, Bernd Fischer, Peter Maass
2012	—	`conf`	A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data. GCB Ilya Chernyavsky, Theodore Alexandrov, Peter Maass, Sergey I. Nikolenko
2012	J	`jnl`	Magnification of Label Maps With a Topology-Preserving Level-Set Method. IEEE Trans. Image Process. Dennis Trede, Theodore Alexandrov, Chen Sagiv, Peter Maass
2012	J	`jnl`	On the Importance of Mathematical Methods for Analysis of MALDI-Imaging Mass Spectrometry Data. J. Integr. Bioinform. Dennis Trede, Jan Hendrik Kobarg, Janina Oetjen, Herbert Thiele, Peter Maass, Theodore Alexandrov
2012	J	`jnl`	Sparsity reconstruction in electrical impedance tomography: An experimental evaluation. J. Comput. Appl. Math. Matthias Gehre, Tobias Kluth, Antti Lipponen, Bangti Jin, Aku Seppänen, Jari P. Kaipio, Peter Maass
2010	J	`jnl`	Adaptive wavelet methods and sparsity reconstruction for inverse heat conduction problems. Adv. Comput. Math. Thomas Bonesky, Stephan Dahlke, Peter Maass, Thorsten Raasch
2009	J	`jnl`	A generalized conditional gradient method and its connection to an iterative shrinkage method. Comput. Optim. Appl. Kristian Bredies, Dirk A. Lorenz, Peter Maass
2009	J	`jnl`	Biomarker discovery in MALDI-TOF serum protein profiles using discrete wavelet transformation. Bioinform. Theodore Alexandrov, Jens Decker, Bart J. A. Mertens, André M. Deelder, Rob A. E. M. Tollenaar, Peter Maass, Herbert Thiele
2008	J	`jnl`	A convex optimisation approach to robust observer-based H Int. J. Model. Identif. Control. Hamid Reza Karimi, Peter Maass
2008	J	`jnl`	Condition monitoring of linear guideways using a matched wavelet approach. Signal Process. Ludger Prünte, Peter Maass, Henning Thielemann
2008	J	`jnl`	The Uncertainty Principle Associated with the Continuous Shearlet Transform. Int. J. Wavelets Multiresolution Inf. Process. Stephan Dahlke, Gitta Kutyniok, Peter Maass, Chen Sagiv, Hans-Georg Stark, Gerd Teschke
2006	—	`conf`	An Optimal Control Problem in Medical Image Processing. Systems, Control, Modeling and Optimization Kristian Bredies, Dirk A. Lorenz, Peter Maass
2003	J	`jnl`	Reconstruction of Wideband Reflectivity Densities by Wavelet Transforms. Adv. Comput. Math. Stephan Dahlke, Peter Maass, Gerd Teschke
2000	J	`jnl`	A two-layered wavelet-based algorithm for efficient lossless and lossy image compression. IEEE Trans. Circuits Syst. Video Technol. Detlev Marpe, Gabi Blattermann, Jens Ricke, Peter Maass
2000	J	`jnl`	Detection and classification of material attributes-a practical application of wavelet analysis. IEEE Trans. Signal Process. Peter Maass, Gerd Teschke, Werner Willmann, Günter Wollmann
1999	J	`jnl`	Fast CG-Based Methods for Tikhonov-Phillips Regularization. SIAM J. Sci. Comput. Andreas Frommer, Peter Maass
1996	J	`jnl`	Wavelet-accelerated regularization methods for hyperthermia treatment planning. Int. J. Imaging Syst. Technol. Peter Maass, Ronny Ramlau
1993	J	`jnl`	Contour reconstruction in 3-D X-ray CT. IEEE Trans. Medical Imaging Alfred K. Louis, Peter Maass
1992	J	`jnl`	Tomographic methods for 2D reconstruction with the double crystal diffractometer. IMPACT Comput. Sci. Eng. Peter Maass, Wolfgang Treimer, U. Feye-Treimer