Line Segmentation and Analysis with Special Interest to the Duct of a Line. - Carola Schönlieb; Kung Chieh Wang (ICVGIP, 2004)

Cahn–Hilliard Inpainting and a Generalization for Grayvalue Images. - Martin Burger 001; Lin He 010; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2009)

Subspace Correction Methods for Total Variation and 1-Minimization. - Massimo Fornasier; Carola-Bibiane Schönlieb (SIAM J. Numer. Anal., 2009)

A convergent overlapping domain decomposition method for total variation minimization. - Massimo Fornasier; Andreas Langer; Carola-Bibiane Schönlieb (Numerische Mathematik, 2010)

Oriented diffusion filtering for enhancing low-quality fingerprint images. - Carsten Gottschlich; Carola-Bibiane Schönlieb (IET Biom., 2012)

Wavelet Decomposition Method for L2//TV-Image Deblurring. - Massimo Fornasier; Yunho Kim; Andreas Langer; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2012)

A Primal-Dual Approach for a Total Variation Wasserstein Flow. - Martin Benning; Luca Calatroni; Bertram Düring; Carola-Bibiane Schönlieb (GSI, 2013)

Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints. - Luca Calatroni; Juan Carlos de los Reyes; Carola-Bibiane Schönlieb (System Modelling and Optimization, 2013)

Anisotropic Third-Order Regularization for Sparse Digital Elevation Models. - Jan Lellmann; Jean-Michel Morel; Carola-Bibiane Schönlieb (SSVM, 2013)

Combined First and Second Order Total Variation Inpainting using Split Bregman. - Konstantinos Papafitsoros; Carola-Bibiane Schönlieb; Bati Sengul (Image Process. Line, 2013)

Bregmanized Domain Decomposition for Image Restoration. - Andreas Langer; Stanley J. Osher; Carola-Bibiane Schönlieb (J. Sci. Comput., 2013)

Non-parametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Forests. - Juheon Lee; Xiaohao Cai; Carola-Bibiane Schönlieb; David Coomes (CoRR, 2014)

A Combined First and Second Order Variational Approach for Image Reconstruction. - Konstantinos Papafitsoros; Carola-Bibiane Schönlieb (J. Math. Imaging Vis., 2014)

Imaging with Kantorovich-Rubinstein Discrepancy. - Jan Lellmann; Dirk A. Lorenz; Carola-Bibiane Schönlieb; Tuomo Valkonen (SIAM J. Imaging Sci., 2014)

Preconditioned ADMM with Nonlinear Operator Constraint. - Martin Benning; Florian Knoll; Carola-Bibiane Schönlieb; Tuomo Valkonen (System Modelling and Optimization, 2015)

Infimal Convolution Regularisation Functionals of BV and Lp Spaces. The Case p=∞. - Martin Burger 001; Konstantinos Papafitsoros; Evangelos Papoutsellis; Carola-Bibiane Schönlieb (System Modelling and Optimization, 2015)

Mapping individual trees from airborne multi-sensor imagery. - Juheon Lee; Xiaohao Cai; Carola-Bibiane Schönlieb; David Coomes (IGARSS, 2015)

Bilevel approaches for learning of variational imaging models. - Luca Calatroni; Cao Chung; Juan Carlos de los Reyes; Carola-Bibiane Schönlieb; Tuomo Valkonen (CoRR, 2015)

The structure of optimal parameters for image restoration problems. - Juan Carlos de los Reyes; Carola-Bibiane Schönlieb; Tuomo Valkonen (CoRR, 2015)

Analysis and Application of a Nonlocal Hessian. - Jan Lellmann; Konstantinos Papafitsoros; Carola Schönlieb; Daniel Spector (SIAM J. Imaging Sci., 2015)

Nonparametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Wooded Landscapes. - Juheon Lee; Xiaohao Cai; Carola-Bibiane Schönlieb; David Coomes (IEEE Trans. Geosci. Remote. Sens., 2015)

Variational Depth From Focus Reconstruction. - Michael Möller 001; Martin Benning; Carola Schönlieb; Daniel Cremers (IEEE Trans. Image Process., 2015)

Partial Differential Equation Methods for Image Inpainting. - Carola-Bibiane Schönlieb (Cambridge University Press, 2016)

A DBN-crf for spectral-spatial classification of hyperspectral data. - Ping Zhong 001; Zhiqiang Gong; Carola-Bibiane Schönlieb (ICPR, 2016)

Guidefill: GPU Accelerated, Artist Guided Geometric Inpainting for 3D Conversion. - L. Robert Hocking; Russell MacKenzie; Carola-Bibiane Schönlieb (CoRR, 2016)

Infimal Convolution Regularisation Functionals of BV and Lp Spaces - Part I: The Finite p Case. - Martin Burger 001; Konstantinos Papafitsoros; Evangelos Papoutsellis; Carola-Bibiane Schönlieb (J. Math. Imaging Vis., 2016)

Individual Tree Species Classification From Airborne Multisensor Imagery Using Robust PCA. - Juheon Lee; Xiaohao Cai; Jan Lellmann; Michele Dalponte; Yadvinder Malhi; Nathalie Butt; Mike Morecroft; Carola-Bibiane Schönlieb; David A. Coomes (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016)

Nonlinear Spectral Image Fusion. - Martin Benning; Michael Möller 001; Raz Z. Nossek; Martin Burger 001; Daniel Cremers; Guy Gilboa; Carola-Bibiane Schönlieb (SSVM, 2017)

Learning Filter Functions in Regularisers by Minimising Quotients. - Martin Benning; Guy Gilboa; Joana Sarah Grah; Carola-Bibiane Schönlieb (SSVM, 2017)

Numerical analysis of shell-based geometric image inpainting algorithms and their semi-implicit extension. - L. Robert Hocking; Thomas Holding; Carola-Bibiane Schönlieb (CoRR, 2017)

A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery. - Juheon Lee; David Coomes; Carola-Bibiane Schönlieb; Xiaohao Cai; Jan Lellmann; Michele Dalponte; Yadvinder Malhi; Nathalie Butt; Mike Morecroft (CoRR, 2017)

Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation. - Leon Bungert; David A. Coomes; Matthias J. Ehrhardt; Jennifer Rasch; Rafael Reisenhofer; Carola-Bibiane Schönlieb (CoRR, 2017)

Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images. - Luca Calatroni; Yves van Gennip; Carola-Bibiane Schönlieb; Hannah M. Rowland; Arjuna Flenner (J. Math. Imaging Vis., 2017)

Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models. - Juan Carlos de los Reyes; Carola-Bibiane Schönlieb; Tuomo Valkonen (J. Math. Imaging Vis., 2017)

Infimal Convolution of Data Discrepancies for Mixed Noise Removal. - Luca Calatroni; Juan Carlos de los Reyes; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2017)

Guidefill: GPU Accelerated, Artist Guided Geometric Inpainting for 3D Conversion of Film. - L. Robert Hocking; Russell MacKenzie; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2017)

Learning to Diversify Deep Belief Networks for Hyperspectral Image Classification. - Ping Zhong 001; Zhiqiang Gong; Shutao Li; Carola-Bibiane Schönlieb (IEEE Trans. Geosci. Remote. Sens., 2017)

Faster FISTA. - Jingwei Liang; Carola-Bibiane Schönlieb (EUSIPCO, 2018)

Peekaboo-Where are the Objects? Structure Adjusting Superpixels. - Georg Maierhofer; Daniel Heydecker; Angelica I. Avilés-Rivero; Samar M. Alsaleh; Carola-Bibiane Schönlieb (ICIP, 2018)

Local Convergence Properties of SAGA/Prox-SVRG and Acceleration. - Clarice Poon; Jingwei Liang; Carola-Bibiane Schoenlieb (ICML, 2018)

Adversarial Regularizers in Inverse Problems. - Sebastian Lunz; Carola Schönlieb; Ozan Öktem (NeurIPS, 2018)

Unveiling the invisible - mathematical methods for restoring and interpreting illuminated manuscripts. - Luca Calatroni; Marie d'Autume; Rob Hocking; Stella Panayotova; Simone Parisotto; Paola Ricciardi; Carola-Bibiane Schönlieb (CoRR, 2018)

Mirror, Mirror, on the Wall, Who's Got the Clearest Image of Them All? - A Tailored Approach to Single Image Reflection Removal. - Daniel Heydecker; Georg Maierhofer; Angelica I. Avilés-Rivero; Qingnan Fan; Carola-Bibiane Schönlieb; Sabine Süsstrunk (CoRR, 2018)

Linkage between Piecewise Constant Mumford-Shah model and ROF model and its virtue in image segmentation. - Xiaohao Cai; Raymond H. Chan; Carola-Bibiane Schönlieb; Gabriele Steidl; Tieyong Zeng (CoRR, 2018)

A multi-contrast MRI approach to thalamus segmentation. - Veronica Corona; Jan Lellmann; Peter J. Nestor; Carola-Bibiane Schoenlieb; Julio Acosta-Cabronero (CoRR, 2018)

Faster PET Reconstruction with Non-Smooth Priors by Randomization and Preconditioning. - Matthias J. Ehrhardt; Pawel Markiewicz; Carola-Bibiane Schönlieb (CoRR, 2018)

Task adapted reconstruction for inverse problems. - Jonas Adler; Sebastian Lunz; Olivier Verdier; Carola-Bibiane Schönlieb; Ozan Öktem (CoRR, 2018)

Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction. - Angelica I. Avilés-Rivero; Guy B. Williams; Martin J. Graves; Carola-Bibiane Schoenlieb (CoRR, 2018)

A Variational Model for Joint Motion Estimation and Image Reconstruction. - Martin Burger 001; Hendrik Dirks; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2018)

Variational Image Regularization with Euler's Elastica Using a Discrete Gradient Scheme. - Torbjørn Ringholm; Jasmina Lazic; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2018)

Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications. - Antonin Chambolle; Matthias J. Ehrhardt; Peter Richtárik; Carola-Bibiane Schönlieb (SIAM J. Optim., 2018)

RainFlow: Optical Flow Under Rain Streaks and Rain Veiling Effect. - Ruoteng Li; Robby T. Tan; Loong Fah Cheong; Angelica I. Avilés-Rivero; Qingnan Fan; Carola Schönlieb (ICCV, 2019)

On the Connection Between Adversarial Robustness and Saliency Map Interpretability. - Christian Etmann; Sebastian Lunz; Peter Maass; Carola Schönlieb (ICML, 2019)

Semi-Supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Nicolas Papadakis; David Coomes; Anita Faul; Carola-Bibiane Schönlieb (IGARSS, 2019)

GraphX $$^ mathbf{ small NET } -$$ -Chest X-Ray Classification Under Extreme Minimal Supervision. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Philip Sellars; Qingnan Fan; Robby T. Tan; Carola-Bibiane Schönlieb (MICCAI (6), 2019)

GANReDL: Medical Image Enhancement Using a Generative Adversarial Network with Real-Order Derivative Induced Loss Functions. - Pan Liu; Chao Li 031; Carola-Bibiane Schönlieb (MICCAI (3), 2019)

Deep learning for inverse imaging problems: some recent approaches (Conference Presentation). - Carola-Bibiane Schönlieb (Image Processing, 2019)

A Total Variation Based Regularizer Promoting Piecewise-Lipschitz Reconstructions. - Martin Burger 001; Yury Korolev; Carola-Bibiane Schönlieb; Christiane Stollenwerk (SSVM, 2019)

Multi-tasking to Correct: Motion-Compensated MRI via Joint Reconstruction and Registration. - Veronica Corona; Angelica I. Avilés-Rivero; Noémie Debroux; Martin J. Graves; Carole Le Guyader; Carola-Bibiane Schönlieb; Guy B. Williams (SSVM, 2019)

Total Directional Variation for Video Denoising. - Simone Parisotto; Carola-Bibiane Schönlieb (SSVM, 2019)

Solving inverse problems using data-driven models. - Simon R. Arridge; Peter Maass; Ozan Öktem; Carola-Bibiane Schönlieb (Acta Numer., 2019)

Three-dimensional Segmentation of Trees Through a Flexible Multi-Class Graph Cut Algorithm (MCGC). - Jonathan V. Williams; Carola-Bibiane Schönlieb; Tom Swinfield; Juheon Lee; Xiaohao Cai; Lan Qie; David A. Coomes (CoRR, 2019)

Deep learning as optimal control problems: models and numerical methods. - Martin Benning; Elena Celledoni; Matthias J. Ehrhardt; Brynjulf Owren; Carola-Bibiane Schönlieb (CoRR, 2019)

Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Samar M. Alsaleh; Robby T. Tan; Carola-Bibiane Schönlieb (CoRR, 2019)

A multi-task U-net for segmentation with lazy labels. - Rihuan Ke; Aurélie Bugeau; Nicolas Papadakis; Peter Schütz; Carola-Bibiane Schönlieb (CoRR, 2019)

GraphXNET-Chest X-Ray Classification Under Extreme Minimal Supervision. - Angelica I. Avilés-Rivero; Nicolas Papadakis; Ruoteng Li; Philip Sellars; Qingnan Fan; Robby T. Tan; Carola-Bibiane Schönlieb (CoRR, 2019)

Joint phase reconstruction and magnitude segmentation from velocity-encoded MRI data. - Veronica Corona; Martin Benning; Lynn F. Gladden; Andi Reci; Andrew J. Sederman; Carola-Bibiane Schoenlieb (CoRR, 2019)

PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds. - Oliver M. Crook; Tim Hurst; Carola-Bibiane Schönlieb; Matthew Thorpe; Konstantinos C. Zygalakis (CoRR, 2019)

Dynamic Spectral Residual Superpixels. - Jianchao Zhang; Angelica I. Avilés-Rivero; Daniel Heydecker; Xiosheng Zhuang; Raymond H. Chan; Carola-Bibiane Schönlieb (CoRR, 2019)

Total Variation Regularisation with Spatially Variable Lipschitz Constraints. - Martin Burger 001; Yury Korolev; Simone Parisotto; Carola-Bibiane Schönlieb (CoRR, 2019)

Deep Reflection Prior. - Qingnan Fan; Yingda Yin; Dongdong Chen 001; Yujie Wang; Angelica I. Avilés-Rivero; Ruoteng Li; Carola-Bibiane Schönlieb; Dani Lischinski; Baoquan Chen (CoRR, 2019)

Equilibria of an anisotropic nonlocal interaction equation: Analysis and numerics. - José A. Carrillo 001; Bertram Düring; Lisa Maria Kreusser; Carola-Bibiane Schönlieb (CoRR, 2019)

Accurate Measurement of Tropical Forest Canopy Heights and Aboveground Carbon Using Structure From Motion. - Tom Swinfield; Jeremy A. Lindsell; Jonathan V. Williams; Rhett D. Harrison; Agustiono; Habibi; Elva Gemita; Carola B. Schönlieb; David A. Coomes (Remote. Sens., 2019)

Stability Analysis of Line Patterns of an Anisotropic Interaction Model. - José A. Carrillo 001; Bertram Düring; Lisa Maria Kreusser; Carola-Bibiane Schönlieb (SIAM J. Appl. Dyn. Syst., 2019)

Linkage Between Piecewise Constant Mumford-Shah Model and Rudin-Osher-Fatemi Model and Its Virtue in Image Segmentation. - Xiaohao Cai; Raymond H. Chan; Carola-Bibiane Schönlieb; Gabriele Steidl; Tieyong Zeng (SIAM J. Sci. Comput., 2019)

Mirror, Mirror, on the Wall, Who's Got the Clearest Image of Them All? - A Tailored Approach to Single Image Reflection Removal. - Daniel Heydecker; Georg Maierhofer; Angelica I. Avilés-Rivero; Qingnan Fan; Dongdong Chen 001; Carola-Bibiane Schönlieb; Sabine Süsstrunk (IEEE Trans. Image Process., 2019)

Microscopy image sequences and annotated kymographs of laser ablation experiments in Drosophila embryos. - Lukas F. Lang; Nilankur Dutta; Elena Scarpa; Bénédicte Sanson; Carola-Bibiane Schönlieb; Jocelyn Étienne (Zenodo, 2019)

Learning to Segment Microscopy Images with Lazy Labels. - Rihuan Ke; Aurélie Bugeau; Nicolas Papadakis; Peter Schütz; Carola-Bibiane Schönlieb (ECCV Workshops (1), 2020)

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems. - Kaixuan Wei; Angelica I. Avilés-Rivero; Jingwei Liang; Ying Fu 001; Carola-Bibiane Schönlieb; Hua Huang 001 (ICML, 2020)

iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems. - Christian Etmann; Rihuan Ke; Carola-Bibiane Schönlieb (MLSP, 2020)

Deeply Learned Spectral Total Variation Decomposition. - Tamara G. Grossmann; Yury Korolev; Guy Gilboa; Carola B. Schönlieb (NeurIPS, 2020)

Two Cycle Learning: Clustering Based Regularisation for Deep Semi-Supervised Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (CoRR, 2020)

Learning Optical Flow for Fast MRI Reconstruction. - Timothée Schmoderer; Angelica I. Avilés-Rivero; Veronica Corona; Noémie Debroux; Carola B. Schönlieb (CoRR, 2020)

iUNets: Fully invertible U-Nets with Learnable Up- and Downsampling. - Christian Etmann; Rihuan Ke; Carola-Bibiane Schönlieb (CoRR, 2020)

On Learned Operator Correction. - Sebastian Lunz; Andreas Hauptmann; Tanja Tarvainen; Carola-Bibiane Schönlieb; Simon R. Arridge (CoRR, 2020)

Variational regularisation for inverse problems with imperfect forward operators and general noise models. - Leon Bungert; Martin Burger 001; Yury Korolev; Carola-Bibiane Schoenlieb (CoRR, 2020)

Unsupervised clustering of Roman pottery profiles from their SSAE representation. - Simone Parisotto; Alessandro Launaro; Ninetta Leone; Carola-Bibiane Schönlieb (CoRR, 2020)

Structure preserving deep learning. - Elena Celledoni; Matthias J. Ehrhardt; Christian Etmann; Robert I. McLachlan; Brynjulf Owren; Carola-Bibiane Schönlieb; Ferdia Sherry (CoRR, 2020)

SLIC-UAV: A Method for monitoring recovery in tropical restoration projects through identification of signature species using UAVs. - Jonathan Williams 003; Carola-Bibiane Schönlieb; Tom Swinfield; Bambang Irawan; Eva Achmad; Muhammad Zudhi; Habibi; Elva Gemita; David A. Coomes (CoRR, 2020)

Ground Truth Free Denoising by Optimal Transport. - Sören Dittmer; Carola-Bibiane Schönlieb; Peter Maass (CoRR, 2020)

Art Speaks Maths, Maths Speaks Art. - Ninetta Leone; Simone Parisotto; Kasia Targonska-Hadzibabic; Spike Bucklow; Alessandro Launaro; Suzanne Reynolds; Carola-Bibiane Schönlieb (CoRR, 2020)

Image reconstruction in dynamic inverse problems with temporal models. - Andreas Hauptmann; Ozan Öktem; Carola Schönlieb (CoRR, 2020)

Learned convex regularizers for inverse problems. - Subhadip Mukherjee; Sören Dittmer; Zakhar Shumaylov; Sebastian Lunz; Ozan Öktem; Carola-Bibiane Schönlieb (CoRR, 2020)

Scanning electron diffraction tomography of strain. - Robert Tovey; Duncan N. Johnstone; Sean M. Collins; William R. B. Lionheart; Paul A. Midgley; Martin Benning; Carola-Bibiane Schönlieb (CoRR, 2020)

Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. - 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; et al. (CoRR, 2020)

A Linear Transportation Lp Distance for Pattern Recognition. - Oliver M. Crook; Mihai Cucuringu; Tim Hurst; Carola-Bibiane Schönlieb; Matthew Thorpe; Konstantinos C. Zygalakis (CoRR, 2020)

Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding. - Veronica Corona; Yehuda Dar; Carola-Bibiane Schönlieb (CoRR, 2020)

TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems. - Kaixuan Wei; Angelica I. Avilés-Rivero; Jingwei Liang; Ying Fu 001; Hua Huang 001; Carola-Bibiane Schönlieb (CoRR, 2020)

Analysis of Artifacts in Shell-Based Image Inpainting: Why They Occur and How to Eliminate Them. - L. Robert Hocking; Thomas Holding; Carola-Bibiane Schönlieb (Found. Comput. Math., 2020)

Bregman Itoh-Abe Methods for Sparse Optimisation. - Martin Benning; Erlend Skaldehaug Riis; Carola-Bibiane Schönlieb (J. Math. Imaging Vis., 2020)

A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis. - Noémie Debroux; John A. D. Aston; Fabien Bonardi; Alistair Forbes; Carole Le Guyader; Marina Romanchikova; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2020)

Higher-Order Total Directional Variation: Imaging Applications. - Simone Parisotto; Jan Lellmann; Simon Masnou; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2020)

Higher-Order Total Directional Variation: Analysis. - Simone Parisotto; Simon Masnou; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2020)

Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (IEEE Trans. Geosci. Remote. Sens., 2020)

3D Segmentation of Trees Through a Flexible Multiclass Graph Cut Algorithm. - Jonathan Williams 003; Carola-Bibiane Schönlieb; Tom Swinfield; Juheon Lee; Xiaohao Cai; Lan Qie; David A. Coomes (IEEE Trans. Geosci. Remote. Sens., 2020)

Variational Osmosis for Non-Linear Image Fusion. - Simone Parisotto; Luca Calatroni; Aurélie Bugeau; Nicolas Papadakis; Carola-Bibiane Schönlieb (IEEE Trans. Image Process., 2020)

Learning the Sampling Pattern for MRI. - Ferdia Sherry; Martin Benning; Juan Carlos de los Reyes; Martin J. Graves; Georg Maierhofer; Guy B. Williams; Carola-Bibiane Schönlieb; Matthias Joachim Ehrhardt (IEEE Trans. Medical Imaging, 2020)

Low resolution scanned text dataset for optical character recognition. - Julian D. Gilbey; Carola-Bibiane Schönlieb (Zenodo, 2020)

Trained tesseract networks for low-resolution optical character recognition. - Julian D. Gilbey; Carola-Bibiane Schönlieb (Zenodo, 2020)

MATLAB/Python Codes for the Image Inpainting Problem. - Simone Parisotto; Carola-Bibiane Schönlieb (Zenodo, 2020)

Adaptive Unsupervised Learning with Enhanced Feature Representation for Intra-tumor Partitioning and Survival Prediction for Glioblastoma. - Yifan Li; Chao Li 031; Yiran Wei 002; Stephen J. Price; Carola-Bibiane Schönlieb; Xi Chen 042 (BrainLes@MICCAI (1), 2021)

Predicting Isocitrate Dehydrogenase Mutation Status in Glioma Using Structural Brain Networks and Graph Neural Networks. - Yiran Wei 002; Yonghao Li; Xi Chen 042; Carola-Bibiane Schönlieb; Chao Li 031; Stephen J. Price (BrainLes@MICCAI (1), 2021)

BrainNetGAN: Data Augmentation of Brain Connectivity Using Generative Adversarial Network for Dementia Classification. - Chao Li 031; Yiran Wei 002; Xi Chen 042; Carola-Bibiane Schönlieb (DGM4MICCAI/DALI@MICCAI, 2021)

End-to-end reconstruction meets data-driven regularization for inverse problems. - Subhadip Mukherjee; Marcello Carioni; Ozan Öktem; Carola-Bibiane Schönlieb (NeurIPS, 2021)

Adversarially Learned Iterative Reconstruction for Imaging Inverse Problems. - Subhadip Mukherjee; Ozan Öktem; Carola-Bibiane Schönlieb (SSVM, 2021)

Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy. - Michael Yeung; Evis Sala; Carola-Bibiane Schönlieb; Leonardo Rundo (Comput. Biol. Medicine, 2021)

3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. - Maureen van Eijnatten; Leonardo Rundo; Kees Joost Batenburg; Felix Lucka; Emma Beddowes; Carlos Caldas; Ferdia A. Gallagher; Evis Sala; Carola-Bibiane Schönlieb; Ramona Woitek (Comput. Methods Programs Biomed., 2021)

Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma. - Chao Li 031; Wenjian Huang; Xi Chen 042; Yiran Wei 002; Stephen J. Price; Carola-Bibiane Schönlieb (CoRR, 2021)

A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation. - Michael Yeung; Evis Sala; Carola-Bibiane Schönlieb; Leonardo Rundo (CoRR, 2021)

Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization. - Christina Runkel; Christian Etmann; Michael Möller 001; Carola-Bibiane Schönlieb (CoRR, 2021)

Equivariant neural networks for inverse problems. - Elena Celledoni; Matthias J. Ehrhardt; Christian Etmann; Brynjulf Owren; Carola-Bibiane Schönlieb; Ferdia Sherry (CoRR, 2021)

Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance). - Jan Stanczuk; Christian Etmann; Lisa Maria Kreusser; Carola-Bibiane Schönlieb (CoRR, 2021)

Efficient Global Optimization of Non-differentiable, Symmetric Objectives for Multi Camera Placement. - Maria L. Hänel; Carola-Bibiane Schönlieb (CoRR, 2021)

Semi-supervised Superpixel-based Multi-Feature Graph Learning for Hyperspectral Image Data. - Madeleine Kotzagiannidis; Carola-Bibiane Schönlieb (CoRR, 2021)

An end-to-end Optical Character Recognition approach for ultra-low-resolution printed text images. - Julian D. Gilbey; Carola-Bibiane Schönlieb (CoRR, 2021)

Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy. - Michael Yeung; Evis Sala; Carola-Bibiane Schönlieb; Leonardo Rundo (CoRR, 2021)

CAFLOW: Conditional Autoregressive Flows. - Georgios Batzolis; Marcello Carioni; Christian Etmann; Soroosh Afyouni; Zoe Kourtzi; Carola-Bibiane Schönlieb (CoRR, 2021)

LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (CoRR, 2021)

Learning convex regularizers satisfying the variational source condition for inverse problems. - Subhadip Mukherjee; Carola-Bibiane Schönlieb; Martin Burger 001 (CoRR, 2021)

Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation. - Michael Yeung; Guang Yang 006; Evis Sala; Carola-Bibiane Schönlieb; Leonardo Rundo (CoRR, 2021)

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence. - Xiang Bai; Hanchen Wang 002; Liya Ma; Yongchao Xu; Jiefeng Gan; Ziwei Fan 005; Fan Yang 038; Ke Ma; Jiehua Yang; Song Bai 001; Chang Shu; Xinyu Zou; et al. (CoRR, 2021)

Conditional Image Generation with Score-Based Diffusion Models. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb; Christian Etmann (CoRR, 2021)

AI-based Reconstruction for Fast MRI - A Systematic Review and Meta-analysis. - Yutong Chen; Carola-Bibiane Schönlieb; Pietro Liò; Tim Leiner; Pier Luigi Dragotti; Gerald Wang; Daniel Rueckert; David N. Firmin; Guang Yang 006 (CoRR, 2021)

Compressed sensing plus motion (CS + M): A new perspective for improving undersampled MR image reconstruction. - Angelica I. Avilés-Rivero; Noémie Debroux; Guy B. Williams; Martin J. Graves; Carola-Bibiane Schönlieb (Medical Image Anal., 2021)

Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution. - Veronica Corona; Angelica I. Avilés-Rivero; Noémie Debroux; Carole Le Guyader; Carola-Bibiane Schönlieb (Medical Image Anal., 2021)

Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction. - Jiulong Liu; Angelica I. Avilés-Rivero; Hui Ji; Carola-Bibiane Schönlieb (Medical Image Anal., 2021)

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. - Xiang Bai; Hanchen Wang 002; Liya Ma; Yongchao Xu; Jiefeng Gan; Ziwei Fan 005; Fan Yang 038; Ke Ma; Jiehua Yang; Song Bai 001; Chang Shu; Xinyu Zou; et al. (Nat. Mach. Intell., 2021)

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. - 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; et al. (Nat. Mach. Intell., 2021)

Radiological tumour classification across imaging modality and histology. - Jia Wu 009; Chao Li 031; Michael Gensheimer 001; Sukhmani Padda; Fumi Kato; Hiroki Shirato; Yiran Wei 002; Carola-Bibiane Schönlieb; Stephen John Price; David A. Jaffray; John V. Heymach; Joel W. Neal; et al. (Nat. Mach. Intell., 2021)

Dynamic spectral residual superpixels. - Jianchao Zhang; Angelica I. Avilés-Rivero; Daniel Heydecker; Xiaosheng Zhuang; Raymond H. Chan; Carola-Bibiane Schönlieb (Pattern Recognit., 2021)

Choose Your Path Wisely: Gradient Descent in a Bregman Distance Framework. - Martin Benning; Marta M. Betcke; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2021)

A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization. - Derek Driggs; Junqi Tang; Jingwei Liang; Mike E. Davies 001; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2021)

On Learned Operator Correction in Inverse Problems. - Sebastian Lunz; Andreas Hauptmann; Tanja Tarvainen; Carola-Bibiane Schönlieb; Simon R. Arridge (SIAM J. Imaging Sci., 2021)

Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks. - Rihuan Ke; Aurélie Bugeau; Nicolas Papadakis; Mark Kirkland; Peter Schütz; Carola-Bibiane Schönlieb (IEEE Trans. Image Process., 2021)

ROCOPOT (ROman COmmonware POTtery) Dataset. - Simone Parisotto; Alessandro Launaro; Ninetta Leone; Carola-Bibiane Schönlieb (Zenodo, 2021)

INLUMINA (INpainting of ilLUminated MINiatures App) Dataset. - Simone Parisotto; Stella Panayotova; Suzanne Reynolds; Carola-Bibiane Schönlieb (Zenodo, 2021)

Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading. - Lipei Zhang; Yiran Wei 002; Ying Fu 001; Stephen J. Price; Carola-Bibiane Schönlieb; Chao Li 031 (BMVC, 2022)

Rethinking Video Rain Streak Removal: A New Synthesis Model and a Deraining Network with Video Rain Prior. - Shuai Wang; Lei Zhu 003; Huazhu Fu; Jing Qin 001; Carola-Bibiane Schönlieb; Wei Feng 005; Song Wang 002 (ECCV (19), 2022)

Stylegan-Induced Data-Driven Regularization for Inverse Problems. - Arthur Conmy; Subhadip Mukherjee; Carola-Bibiane Schönlieb (ICASSP, 2022)

Collaborative Learning of Images and Geometrics for Predicting Isocitrate Dehydrogenase Status of Glioma. - Yiran Wei 002; Chao Li 031; Xi Chen 042; Carola-Bibiane Schönlieb; Stephen J. Price (ISBI, 2022)

Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation. - Michael Yeung; Leonardo Rundo; Evis Sala; Carola-Bibiane Schönlieb; Guang Yang 006 (ISBI, 2022)

Multi-modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification. - Angelica I. Avilés-Rivero; Christina Runkel; Nicolas Papadakis; Zoe Kourtzi; Carola-Bibiane Schönlieb (MICCAI (3), 2022)

Multi-task Learning-Driven Volume and Slice Level Contrastive Learning for 3D Medical Image Classification. - Jiayuan Zhu; Shujun Wang; Jinzheng He; Carola-Bibiane Schönlieb; Lequan Yu (CMMCA@MICCAI, 2022)

Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting. - Lihao Liu; Chenyang Hong; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (MIUA, 2022)

HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation. - Hankui Peng; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (WACV, 2022)

You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration. - Lihao Liu; Zhening Huang; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (WBIR, 2022)

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation. - Michael Yeung; Evis Sala; Carola-Bibiane Schönlieb; Leonardo Rundo (Comput. Medical Imaging Graph., 2022)

Γ-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation. - Irene Fonseca; Lisa Maria Kreusser; Carola-Bibiane Schönlieb; Matthew Thorpe (CoRR, 2022)

Mutual Contrastive Learning to Disentangle Whole Slide Image Representations for Glioma Grading. - Lipei Zhang; Yiran Wei 002; Ying Fu 001; Stephen J. Price; Carola-Bibiane Schönlieb; Chao Li 031 (CoRR, 2022)

Predicting conversion of mild cognitive impairment to Alzheimer's disease. - Yiran Wei 002; Stephen J. Price; Carola-Bibiane Schönlieb; Chao Li 031 (CoRR, 2022)

PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation. - Lihao Liu; Zhening Huang; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2022)

Unsupervised Clustering of Roman Potsherds via Variational Autoencoders. - Simone Parisotto; Ninetta Leone; Carola-Bibiane Schönlieb; Alessandro Launaro (CoRR, 2022)

Unsupervised Learning of the Total Variation Flow. - Tamara G. Grossmann; Sören Dittmer; Yury Korolev; Carola-Bibiane Schönlieb (CoRR, 2022)

Learned reconstruction with convergence guarantees. - Subhadip Mukherjee; Andreas Hauptmann; Ozan Öktem; Marcelo Pereyra; Carola-Bibiane Schönlieb (CoRR, 2022)

Classification of datasets with imputed missing values: does imputation quality matter? - Tolou Shadbahr; Michael Roberts; Jan Stanczuk; Julian D. Gilbey; Philip Teare; Sören Dittmer; Matthew Thorpe; Ramón Viñas Torné 001; Evis Sala; Pietro Lió; Mishal Patel; AIX-COVNET Collaboration; et al. (CoRR, 2022)

Non-Uniform Diffusion Models. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb; Christian Etmann (CoRR, 2022)

Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning. - Junqi Tang; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb (CoRR, 2022)

Accelerating Deep Unrolling Networks via Dimensionality Reduction. - Junqi Tang; Subhadip Mukherjee; Carola-Bibiane Schönlieb (CoRR, 2022)

Imaging with Equivariant Deep Learning. - Dongdong Chen 004; Mike E. Davies 001; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Ferdia Sherry; Julián Tachella (CoRR, 2022)

Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels. - Jan Oscar Cross-Zamirski; Guy B. Williams; Elizabeth Mouchet; Carola-Bibiane Schönlieb; Riku Turkki; Yinhai Wang (CoRR, 2022)

Navigating the challenges in creating complex data systems: a development philosophy. - 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 (CoRR, 2022)

Maximum Entropy on the Mean and the Cramér Rate Function in Statistical Estimation and Inverse Problems: Properties, Models, and Algorithms. - Yakov Vaisbourd; Rustum Choksi; Ariel Goodwin; Tim Hoheisel; Carola-Bibiane Schönlieb (CoRR, 2022)

On Krylov Methods for Large Scale CBCT Reconstruction. - Malena Sabate Landman; Ander Biguri; Sepideh Hatamikia; Richard P. Boardman; John A. D. Aston; Carola-Bibiane Schönlieb (CoRR, 2022)

Your diffusion model secretly knows the dimension of the data manifold. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb (CoRR, 2022)

A Geometric Integration Approach to Nonsmooth, Nonconvex Optimisation. - Erlend Skaldehaug Riis; Matthias J. Ehrhardt; G. R. W. Quispel; Carola-Bibiane Schönlieb (Found. Comput. Math., 2022)

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions. - Yang Nan 002; Javier Del Ser; Simon Walsh; Carola Schönlieb; Michael Roberts; Ian Selby; Kit Howard; John Owen; Jon Neville; Julien Guiot; Benoit Ernst; Ana Pastor; et al. (Inf. Fusion, 2022)

Image Reconstruction in Light-Sheet Microscopy: Spatially Varying Deconvolution and Mixed Noise. - Bogdan Toader; Jérôme Boulanger; Yury Korolev; Martin O. Lenz; James Manton; Carola-Bibiane Schönlieb; Leila Muresan (J. Math. Imaging Vis., 2022)

On Biased Stochastic Gradient Estimation. - Derek Driggs; Jingwei Liang; Carola-Bibiane Schönlieb (J. Mach. Learn. Res., 2022)

TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems. - Kaixuan Wei; Angelica I. Avilés-Rivero; Jingwei Liang; Ying Fu 001; Hua Huang 001; Carola-Bibiane Schönlieb (J. Mach. Learn. Res., 2022)

Beyond fine-tuning: Classifying high resolution mammograms using function-preserving transformations. - Tao Wei; Angelica I. Avilés-Rivero; Shuo Wang 011; Yuan Huang 009; Fiona J. Gilbert; Carola-Bibiane Schönlieb; Chang Wen Chen (Medical Image Anal., 2022)

Accelerating variance-reduced stochastic gradient methods. - Derek Driggs; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb (Math. Program., 2022)

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. - Xiang Bai; Hanchen Wang 002; Liya Ma; Yongchao Xu; Jiefeng Gan; Ziwei Fan 005; Fan Yang 038; Ke Ma; Jiehua Yang; Song Bai 001; Chang Shu; Xinyu Zou; et al. (Nat. Mach. Intell., 2022)

Unsupervised Image Restoration Using Partially Linear Denoisers. - Rihuan Ke; Carola-Bibiane Schönlieb (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. - Yutong Chen; Carola-Bibiane Schönlieb; Pietro Liò; Tim Leiner; Pier Luigi Dragotti; Ge Wang 001; Daniel Rueckert; David N. Firmin; Guang Yang 006 (Proc. IEEE, 2022)

GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays. - Angelica I. Avilés-Rivero; Philip Sellars; Carola-Bibiane Schönlieb; Nicolas Papadakis (Pattern Recognit., 2022)

Improving "Fast Iterative Shrinkage-Thresholding Algorithm": Faster, Smarter, and Greedier. - Jingwei Liang; Tao Luo; Carola-Bibiane Schönlieb (SIAM J. Sci. Comput., 2022)

Semi-Supervised Superpixel-Based Multi-Feature Graph Learning for Hyperspectral Image Data. - Madeleine S. Kotzagiannidis; Carola-Bibiane Schönlieb (IEEE Trans. Geosci. Remote. Sens., 2022)

A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation. - Rihuan Ke; Angelica I. Avilés-Rivero; Saurabh Pandey; Saikumar Reddy; Carola-Bibiane Schönlieb (IEEE Trans. Image Process., 2022)

ROCOPOT (ROman COmmonware POTtery) Dataset. - Simone Parisotto; Alessandro Launaro; Ninetta Leone; Carola-Bibiane Schönlieb (Zenodo, 2022)

SCOTCH and SODA: A Transformer Video Shadow Detection Framework. - Lihao Liu; Jean Prost; Lei Zhu 003; Nicolas Papadakis; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CVPR, 2023)

Robust Data-Driven Accelerated Mirror Descent. - Hong Ye Tan; Subhadip Mukherjee; Junqi Tang; Andreas Hauptmann; Carola-Bibiane Schönlieb (ICASSP, 2023)

Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels. - Jan Oscar Cross-Zamirski; Praveen Anand; Guy B. Williams; Elizabeth Mouchet; Yinhai Wang; Carola-Bibiane Schönlieb (ICCV (Workshops), 2023)

ViGU: Vision GNN U-Net for fast MRI. - Jiahao Huang; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Guang Yang 006 (ISBI, 2023)

Expectation-Maximization Regularised Deep Learning for Tumour Segmentation. - Chao Li 031; Wenjian Huang; Xi Chen 042; Yiran Wei 002; Lipei Zhang; Jianguo Zhang; Stephen J. Price; Carola-Bibiane Schönlieb (ISBI, 2023)

Predicting Conversion of Mild Cognitive Impairment to Alzheimer's Disease by Modelling Healthy Ageing Trajectories. - Yiran Wei 002; Xi Chen 042; Carola-Bibiane Schönlieb; Stephen J. Price; Chao Li 031 (ISBI, 2023)

CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI? - Jiahao Huang; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Guang Yang 006 (MICCAI (10), 2023)

G-CNN: Adaptive Geometric Convolutional Neural Networks for MRI-Based Skull Stripping. - Yifan Li; Chao Li 031; Yiran Wei 002; Stephen J. Price; Carola-Bibiane Schönlieb; Xi Chen 042 (CMMCA@MICCAI, 2023)

DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification. - Yijun Yang; Huazhu Fu; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Lei Zhu 003 (MICCAI (6), 2023)

Learning Posterior Distributions in Underdetermined Inverse Problems. - Christina Runkel; Michael Möller 001; Carola-Bibiane Schönlieb; Christian Etmann (SSVM, 2023)

Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition Through the Lens of Robustness. - Yanqi Cheng; Lihao Liu; Shujun Wang; Yueming Jin; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (TML4H, 2023)

Can Physics-Informed Neural Networks beat the Finite Element Method? - Tamara G. Grossmann; Urszula Julia Komorowska; Jonas Latz; Carola-Bibiane Schönlieb (CoRR, 2023)

Hidden Knowledge: Mathematical Methods for the Extraction of the Fingerprint of Medieval Paper from Digital Images. - Tamara G. Grossmann; Carola-Bibiane Schönlieb; Orietta Da Rold (CoRR, 2023)

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting. - Simon Graham; Quoc Dang Vu; Mostafa Jahanifar; Martin Weigert 001; Uwe Schmidt; Wenhua Zhang; Jun Zhang 018; Sen Yang 006; Jinxi Xiang; Xiyue Wang; Josef Lorenz Rumberger; Elias Baumann; et al. (CoRR, 2023)

Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation. - Jing Zou; Noémie Debroux; Lihao Liu; Jing Qin 001; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

HGIB: Prognosis for Alzheimer's Disease via Hypergraph Information Bottleneck. - Shujun Wang; Angelica I. Avilés-Rivero; Zoe Kourtzi; Carola-Bibiane Schönlieb (CoRR, 2023)

Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study. - Jiahao Huang; Pedro F. Ferreira; Lichao Wang; Yinzhe Wu 001; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Andrew D. Scott; Zohya Khalique; Maria Dwornik; Ramyah Rajakulasingam; Ranil De Silva; Dudley J. Pennell; et al. (CoRR, 2023)

NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems. - Ziruo Cai; Junqi Tang; Subhadip Mukherjee; Jinglai Li; Carola-Bibiane Schönlieb; Xiaoqun Zhang (CoRR, 2023)

Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb (CoRR, 2023)

Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data. - 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 (CoRR, 2023)

Designing Stable Neural Networks using Convex Analysis and ODEs. - Ferdia Sherry; Elena Celledoni; Matthias J. Ehrhardt; Davide Murari; Brynjulf Owren; Carola-Bibiane Schönlieb (CoRR, 2023)

Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks. - Chaoyu Liu; Zhonghua Qiao; Chao Li 031; Carola-Bibiane Schönlieb (CoRR, 2023)

Reinterpreting survival analysis in the universal approximator age. - Sören Dittmer; Michael Roberts; Jacobus Preller; AIX-COVNET Collaboration; James H. F. Rudd; John A. D. Aston; Carola-Bibiane Schönlieb (CoRR, 2023)

MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening. - Yijun Yang; Shujun Wang; Lihao Liu; Sarah Hickman; Fiona J. Gilbert; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

Riemannian geometry for efficient analysis of protein dynamics data. - Willem Diepeveen; Carlos Esteve Yagüe; Jan Lellmann; Ozan Öktem; Carola-Bibiane Schönlieb (CoRR, 2023)

Bang and the Artefacts are Gone! Rapid Artefact Removal and Tissue Segmentation in Haematoxylin and Eosin Stained Biopsies. - B. A. Schreiber; J. Denholm; F. Jaeckle; M. J. Arends; Kim M. Branson; Carola-Bibiane Schönlieb; E. J. Soilleux (CoRR, 2023)

Recent Methodological Advances in Federated Learning for Healthcare. - 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; et al. (CoRR, 2023)

Provably Convergent Data-Driven Convex-Nonconvex Regularization. - Zakhar Shumaylov; Jeremy Budd; Subhadip Mukherjee; Carola-Bibiane Schönlieb (CoRR, 2023)

Beyond U: Making Diffusion Models Faster & Lighter. - Sergio Calvo-Ordoñez; Jiahao Huang; Lipei Zhang; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks. - Moshe Eliasof; Davide Murari; Ferdia Sherry; Carola-Bibiane Schönlieb (CoRR, 2023)

Traffic Video Object Detection using Motion Prior. - Lihao Liu; Yanqi Cheng; Dongdong Chen 004; Jing He; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations. - Zhenda Shen; Yanqi Cheng; Raymond H. Chan; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

Closing the ODE-SDE gap in score-based diffusion models through the Fokker-Planck equation. - Teo Deveney; Jan Stanczuk; Lisa Maria Kreusser; Chris J. Budd; Carola-Bibiane Schönlieb (CoRR, 2023)

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. - Lihao Liu; Yanqi Cheng; Zhongying Deng; Shujun Wang; Dongdong Chen 004; Xiaowei Hu 001; Pietro Liò; Carola-Bibiane Schönlieb; Angelica E. Avilés-Rivero (CoRR, 2023)

A Continuous-time Stochastic Gradient Descent Method for Continuous Data. - Kexin Jin; Jonas Latz; Chenguang Liu; Carola-Bibiane Schönlieb (J. Mach. Learn. Res., 2023)

Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning. - Dongdong Chen 004; Mike E. Davies 001; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Ferdia Sherry; Julián Tachella (IEEE Signal Process. Mag., 2023)

Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications. - Subhadip Mukherjee; Andreas Hauptmann; Ozan Öktem; Marcelo Pereyra; Carola-Bibiane Schönlieb (IEEE Signal Process. Mag., 2023)

S $^3$ Net: Self-Supervised Self-Ensembling Network for Semi-Supervised RGB-D Salient Object Detection. - Lei Zhu 003; Xiaoqiang Wang 007; Ping Li 016; Xin Yang 011; Qing Zhang 006; Weiming Wang 002; Carola-Bibiane Schönlieb; C. L. Philip Chen (IEEE Trans. Multim., 2023)

Guest Editorial Special Issue on Geometric Deep Learning in Medical Imaging. - Huazhu Fu; Yitian Zhao; Pew-Thian Yap; Carola-Bibiane Schönlieb; Alejandro F. Frangi (IEEE Trans. Medical Imaging, 2023)

Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation. - Michael Yeung; Leonardo Rundo; Yang Nan 002; Evis Sala; Carola-Bibiane Schönlieb; Guang Yang 006 (J. Digit. Imaging, 2023)

Joint Reconstruction-Segmentation on Graphs. - Jeremy Budd; Yves van Gennip; Jonas Latz; Simone Parisotto; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2023)

Dynamical Systems-Based Neural Networks. - Elena Celledoni; Davide Murari; Brynjulf Owren; Carola-Bibiane Schönlieb; Ferdia Sherry (SIAM J. Sci. Comput., 2023)

Data-Driven Mirror Descent with Input-Convex Neural Networks. - Hong Ye Tan; Subhadip Mukherjee; Junqi Tang; Carola-Bibiane Schönlieb (SIAM J. Math. Data Sci., 2023)

Navigating the development challenges in creating complex data systems. - 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; et al. (Nat. Mac. Intell., 2023)

Regularizing Orientation Estimation in Cryogenic Electron Microscopy Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds. - Willem Diepeveen; Jan Lellmann; Ozan Öktem; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2023)

Multi-Modal Learning for Predicting the Genotype of Glioma. - Yiran Wei 002; Xi Chen 042; Lei Zhu 003; Lipei Zhang; Carola-Bibiane Schönlieb; Stephen J. Price; Chao Li 031 (IEEE Trans. Medical Imaging, 2023)

On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. - Moshe Eliasof; Eldad Haber; Eran Treister; Carola-Bibiane Schönlieb (AISTATS, 2024)

Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach. - Moshe Eliasof; Davide Murari; Ferdia Sherry; Carola-Bibiane Schönlieb (ECAI, 2024)

Data-Driven Convex Regularizers for Inverse Problems. - Subhadip Mukherjee; Sören Dittmer; Zakhar Shumaylov; Sebastian Lunz; Ozan Öktem; Carola B. Schönlieb (ICASSP, 2024)

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations. - Andrey Bryutkin; Jiahao Huang; Zhongying Deng; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (ICML, 2024)

Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation. - Zakhar Shumaylov; Jeremy Budd; Subhadip Mukherjee; Carola-Bibiane Schönlieb (ICML, 2024)

Diffusion Models Encode the Intrinsic Dimension of Data Manifolds. - Jan Stanczuk; Georgios Batzolis; Teo Deveney; Carola-Bibiane Schönlieb (ICML, 2024)

Optimised Propainter for Video Diminished Reality Inpainting. - Pengze Li; Lihao Liu; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (ISBI, 2024)

A Study on the Adequacy of Common IQA Measures for Medical Images. - 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; et al. (MICAD, 2024)

Spatiotemporal Graph Neural Network Modelling Perfusion MRI. - Ruodan Yan; Carola-Bibiane Schönlieb; Chao Li 031 (MICCAI (2), 2024)

Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation. - Lipei Zhang; Yanqi Cheng; Lihao Liu; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (MICCAI (12), 2024)

Continuous Learned Primal Dual. - Christina Runkel; Ander Biguri; Carola-Bibiane Schönlieb (MLSP, 2024)

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. - Lihao Liu; Yanqi Cheng; Zhongying Deng; Shujun Wang; Dongdong Chen 001; Xiaowei Hu 001; Pietro Liò; Carola-Bibiane Schönlieb; Angelica E. Avilés-Rivero (ACM Multimedia, 2024)

GRANOLA: Adaptive Normalization for Graph Neural Networks. - Moshe Eliasof; Beatrice Bevilacqua; Carola-Bibiane Schönlieb; Haggai Maron (NeurIPS, 2024)

DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. - Krishna Sri Ipsit Mantri; Xinzhi Wang; Carola-Bibiane Schönlieb; Bruno Ribeiro 001; Beatrice Bevilacqua; Moshe Eliasof (NeurIPS, 2024)

Can generative AI replace immunofluorescent staining processes? A comparison study of synthetically generated cellpainting images from brightfield. - Xiaodan Xing; Siofra Murdoch; Chunling Tang; Giorgos Papanastasiou; Jan Oscar Cross-Zamirski; Yunzhe Guo; Xianglu Xiao; Carola-Bibiane Schönlieb; Yinhai Wang; Guang Yang 006 (Comput. Biol. Medicine, 2024)

Multi-objective Bayesian optimization with enhanced features for adaptively improved glioblastoma partitioning and survival prediction. - Yifan Li; Chao Li 031; Yiran Wei 002; Stephen J. Price; Carola-Bibiane Schönlieb; Xi Chen 042 (Comput. Medical Imaging Graph., 2024)

Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI. - Simone Saitta; Marcello Carioni; Subhadip Mukherjee; Carola-Bibiane Schönlieb; Alberto Redaelli (Comput. Methods Programs Biomed., 2024)

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations. - Andrey Bryutkin; Jiahao Huang; Zhongying Deng; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica E. Avilés-Rivero (CoRR, 2024)

MambaMIR: An Arbitrary-Masked Mamba for Joint Medical Image Reconstruction and Uncertainty Estimation. - Jiahao Huang; Liutao Yang; Fanwen Wang; Yinzhe Wu 001; Yang Nan 002; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Daoqiang Zhang; Guang Yang 006 (CoRR, 2024)

Bilevel Hypergraph Networks for Multi-Modal Alzheimer's Diagnosis. - Angelica I. Avilés-Rivero; Chun-Wun Cheng; Zhongying Deng; Zoe Kourtzi; Carola-Bibiane Schönlieb (CoRR, 2024)

Tackling Graph Oversquashing by Global and Local Non-Dissipativity. - Alessio Gravina; Moshe Eliasof; Claudio Gallicchio; Davide Bacciu; Carola-Bibiane Schönlieb (CoRR, 2024)

When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI. - Xiaodan Xing; Fadong Shi; Jiahao Huang; Yinzhe Wu 001; Yang Nan 002; Sheng Zhang 024; Yingying Fang; Mike Roberts; Carola-Bibiane Schönlieb; Javier Del Ser; Guang Yang 006 (CoRR, 2024)

Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba. - Jiahao Huang; Liutao Yang; Fanwen Wang; Yang Nan 002; Weiwen Wu; Chengyan Wang; Kuangyu Shi; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Daoqiang Zhang; Guang Yang 006 (CoRR, 2024)

FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimization. - Fan Zhang; Carlos Esteve Yagüe; Sören Dittmer; Carola-Bibiane Schönlieb; Michael Roberts (CoRR, 2024)

A study of why we need to reassess full reference image quality assessment with medical images. - 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; et al. (CoRR, 2024)

A study on the adequacy of common IQA measures for medical images. - 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; et al. (CoRR, 2024)

Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems. - Chaoyan Huang; Zhongming Wu; Yanqi Cheng; Tieyong Zeng; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2024)

G-Adaptive mesh refinement - leveraging graph neural networks and differentiable finite element solvers. - James Rowbottom; Georg Maierhofer; Teo Deveney; Katharina Schratz; Pietro Liò; Carola-Bibiane Schönlieb; Chris J. Budd (CoRR, 2024)

NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning. - Yi Zhang 109; Chun-Wun Cheng; Ke Yu; Zhihai He; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2024)

Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps. - Jakob Träuble; Lucy V. Hiscox; Curtis L. Johnson; Carola-Bibiane Schönlieb; Gabriele Kaminski Schierle; Angelica I. Avilés-Rivero (CoRR, 2024)

Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. - Hong Ye Tan; Subhadip Mukherjee; Junqi Tang; Carola-Bibiane Schönlieb (CoRR, 2024)

Learned denoising with simulated and experimental low-dose CT data. - Maximilian B. Kiss; Ander Biguri; Carola-Bibiane Schönlieb; Kees Joost Batenburg; Felix Lucka (CoRR, 2024)

Deep Generative Classification of Blood Cell Morphology. - 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; et al. (CoRR, 2024)

Nested Bregman Iterations for Decomposition Problems. - Tobias Wolf; Derek Driggs; Kostas Papafitsoros; Elena Resmerita; Carola-Bibiane Schönlieb (CoRR, 2024)

Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling. - Stathis Megas; Daniel G. Chen; Krzysztof Polanski; Moshe Eliasof; Carola-Bibiane Schönlieb; Sarah A. Teichmann (CoRR, 2024)

Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space. - Yangming Li; Chieh-Hsin Lai; Carola-Bibiane Schönlieb; Yuki Mitsufuji; Stefano Ermon (CoRR, 2024)

Score-based pullback Riemannian geometry. - Willem Diepeveen; Georgios Batzolis; Zakhar Shumaylov; Carola-Bibiane Schönlieb (CoRR, 2024)

Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs. - Chun-Wun Cheng; Jiahao Huang; Yi Zhang 109; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2024)

Pullback Flow Matching on Data Manifolds. - Friso de Kruiff; Erik J. Bekkers; Ozan Öktem; Carola-Bibiane Schönlieb; Willem Diepeveen (CoRR, 2024)

Hamiltonian Matching for Symplectic Neural Integrators. - Priscilla Canizares; Davide Murari; Carola-Bibiane Schönlieb; Ferdia Sherry; Zakhar Shumaylov (CoRR, 2024)

On the Utilization of Unique Node Identifiers in Graph Neural Networks. - Maya Bechler-Speicher; Moshe Eliasof; Carola-Bibiane Schönlieb; Ran Gilad-Bachrach; Amir Globerson (CoRR, 2024)

You KAN Do It in a Single Shot: Plug-and-Play Methods with Single-Instance Priors. - Yanqi Cheng; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2024)

Benchmarking learned algorithms for computed tomography image reconstruction tasks. - Maximilian B. Kiss; Ander Biguri; Zakhar Shumaylov; Ferdia Sherry; Kees Joost Batenburg; Carola-Bibiane Schönlieb; Felix Lucka (CoRR, 2024)

TIGRE v3: Efficient and easy to use iterative computed tomographic reconstruction toolbox for real datasets. - 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; et al. (CoRR, 2024)

Stochastic Multiresolution Image Sketching for Inverse Imaging Problems. - Alessandro Perelli; Carola-Bibiane Schönlieb; Matthias J. Ehrhardt (CoRR, 2024)

Symplectic Neural Flows for Modeling and Discovery. - Priscilla Canizares; Davide Murari; Carola-Bibiane Schönlieb; Ferdia Sherry; Zakhar Shumaylov (CoRR, 2024)

Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs. - Fabrizio Frasca; Fabian Jogl; Moshe Eliasof; Matan Ostrovsky; Carola-Bibiane Schönlieb; Thomas Gärtner 001; Haggai Maron (CoRR, 2024)

The curious case of the test set AUROC. - Michael Roberts; Alon Hazan; Sören Dittmer; James H. F. Rudd; Carola-Bibiane Schönlieb (Nat. Mac. Intell., 2024)

Publisher Correction: The curious case of the test set AUROC. - Michael Roberts; Alon Hazan; Sören Dittmer; James H. F. Rudd; Carola-Bibiane Schönlieb (Nat. Mac. Intell., 2024)

Recent methodological advances in federated learning for healthcare. - 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; et al. (Patterns, 2024)

NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems. - Ziruo Cai; Junqi Tang; Subhadip Mukherjee; Jinglai Li; Carola-Bibiane Schönlieb; Xiaoqun Zhang (SIAM J. Imaging Sci., 2024)

Practical Acceleration of the Condat-Vũ Algorithm. - Derek Driggs; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Junqi Tang (SIAM J. Imaging Sci., 2024)

Proximal Langevin Sampling with Inexact Proximal Mapping. - Matthias J. Ehrhardt; Lorenz Kuger; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2024)

Provably Convergent Plug-and-Play Quasi-Newton Methods. - Hong Ye Tan; Subhadip Mukherjee; Junqi Tang; Carola-Bibiane Schönlieb (SIAM J. Imaging Sci., 2024)

The Missing U for Efficient Diffusion Models. - Sergio Calvo-Ordoñez; Chun-Wun Cheng; Jiahao Huang; Lipei Zhang; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2024)

Continuous U-Net: Faster, Greater and Noiseless. - Chun-Wun Cheng; Christina Runkel; Lihao Liu; Raymond H. Chan; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2024)

Single-Shot Plug-and-Play Methods for Inverse Problems. - Yanqi Cheng; Lipei Zhang; Zhenda Shen; Shujun Wang; Lequan Yu; Raymond H. Chan; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2024)

NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning. - Zhongying Deng; Rihuan Ke; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2024)

Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. - Hong Ye Tan; Ziruo Cai; Marcelo Pereyra; Subhadip Mukherjee; Junqi Tang; Carola-Bibiane Schönlieb (Trans. Mach. Learn. Res., 2024)

Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration. - Hong Ye Tan; Subhadip Mukherjee; Junqi Tang; Carola-Bibiane Schönlieb (Trans. Mach. Learn. Res., 2024)

Contrastive Learning with Adaptive Neighborhoods for Brain Age Prediction on 3D Stiffness Maps. - Jakob Träuble; Lucy V. Hiscox; Curtis L. Johnson; Carola-Bibiane Schönlieb; Gabriele Kaminski Schierle; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2024)

A linear transportation Lp distance for pattern recognition. - Oliver M. Crook; Mihai Cucuringu; Tim Hurst; Carola-Bibiane Schönlieb; Matthew Thorpe; Konstantinos C. Zygalakis (Pattern Recognit., 2024)

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification. - Philip Sellars; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (IEEE Trans. Neural Networks Learn. Syst., 2024)

Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes. - Antonin Chambolle; Claire Delplancke; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb; Junqi Tang (J. Math. Imaging Vis., 2024)

Learning Regularization for Graph Inverse Problems. - Moshe Eliasof; Md Shahriar Rahim Siddiqui; Carola-Bibiane Schönlieb; Eldad Haber (AAAI, 2025)

On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems. - Alessio Gravina; Moshe Eliasof; Claudio Gallicchio; Davide Bacciu; Carola-Bibiane Schönlieb (AAAI, 2025)

Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations. - Yi Zhang 109; Chun-Wun Cheng; Junyi He; Zhihai He; Carola-Bibiane Schönlieb; Yuyan Chen; Angelica I. Avilés-Rivero (AAAI, 2025)

DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations. - Krishna Sri Ipsit Mantri; Carola-Bibiane Schönlieb; Bruno Ribeiro 001; Chaim Baskin; Moshe Eliasof (CVPR, 2025)

Training Data Reconstruction: Privacy due to Uncertainty? - Christina Runkel; Kanchana Vaishnavi Gandikota; Jonas Geiping; Carola-Bibiane Schönlieb; Michael Moeller 001 (CVPR Workshops, 2025)

Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems. - Junqi Tang; Subhadip Mukherjee; Carola-Bibiane Schönlieb (ICASSP, 2025)

Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement. - Stathis Megas; Daniel G. Chen; Krzysztof Polanski; Moshe Eliasof; Carola-Bibiane Schönlieb; Sarah A. Teichmann (ICLR, 2025)

Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. - Zakhar Shumaylov; Peter Zaika; James Rowbottom; Ferdia Sherry; Melanie Weber 001; Carola-Bibiane Schönlieb (ICLR, 2025)

Parameter Choices in Haarpsi for IQA with Medical Images. - 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; et al. (ISBI, 2025)

Enhanced Denoising and Convergent Regularisation Using Tweedie Scaling. - Naïl Khelifa; Carola-Bibiane Schönlieb; Ferdia Sherry (SSVM (1), 2025)

Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising. - Junqi Tang; Matthias J. Ehrhardt; Carola-Bibiane Schönlieb (SSVM (2), 2025)

Motion Constrained Point Cloud Matching for Maritime Tracking. - Nicholas Dalhaug; Martin Baerveldt; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Annette Stahl; Rudolf Mester; Edmund Førland Brekke (IEEE Access, 2025)

Artificial immunofluorescence in a flash: Rapid synthetic imaging from brightfield through residual diffusion. - 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; et al. (Neurocomputing, 2025)

Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba. - Jiahao Huang; Liutao Yang; Fanwen Wang; Yinzhe Wu 001; Yang Nan 002; Weiwen Wu; Chengyan Wang; Kuangyu Shi; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Daoqiang Zhang; Guang Yang 006 (Medical Image Anal., 2025)

Learning homeomorphic image registration via conformal-invariant hyperelastic regularisation. - Jing Zou; Noémie Debroux; Lihao Liu; Jing Qin 001; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Medical Image Anal., 2025)

On the caveats of AI autophagy. - Xiaodan Xing; Fadong Shi; Jiahao Huang; Yinzhe Wu 001; Yang Nan 002; Sheng Zhang 024; Yingying Fang; Michael Roberts; Carola-Bibiane Schönlieb; Javier Del Ser; Guang Yang 006 (Nat. Mac. Intell., 2025)

Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation. - Chaoyu Liu; Zhonghua Qiao; Chao Li 031; Carola-Bibiane Schönlieb (SIAM J. Math. Data Sci., 2025)

Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction. - Liutao Yang; Jiahao Huang; Yingying Fang; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Daoqiang Zhang; Guang Yang 006 (IEEE Trans. Instrum. Meas., 2025)

Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey. - Amer Essakine; Yanqi Cheng; Chun-Wun Cheng; Lipei Zhang; Zhongying Deng; Lei Zhu 003; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2025)

Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. - Billy Joe Franks; Moshe Eliasof; Semih Cantürk; Guy Wolf; Carola-Bibiane Schönlieb; Sophie Fellenz; Marius Kloft (Trans. Mach. Learn. Res., 2025)

Neural varifolds: an aggregate representation for quantifying the geometry of point clouds. - Juheon Lee; Xiaohao Cai; Carola-Bibiane Schönlieb; Simon Masnou (Trans. Mach. Learn. Res., 2025)

GRAMA: Adaptive Graph Autoregressive Moving Average Models. - Moshe Eliasof; Alessio Gravina; Andrea Ceni; Claudio Gallicchio; Davide Bacciu; Carola-Bibiane Schönlieb (CoRR, 2025)

Inverse Evolution Data Augmentation for Neural PDE Solvers. - Chaoyu Liu; Chris J. Budd; Carola-Bibiane Schönlieb (CoRR, 2025)

Generative Unordered Flow for Set-Structured Data Generation. - Yangming Li; Carola-Bibiane Schönlieb (CoRR, 2025)

Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis. - Xu Chen; Yuan Huang 009; Benn Jessney; Jason Sangha; Sophie Gu; Carola-Bibiane Schönlieb; Martin Bennett; Michael Roberts (CoRR, 2025)

Contrastive Registration for Unsupervised Medical Image Segmentation. - Lihao Liu; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb (IEEE Trans. Neural Networks Learn. Syst., 2025)

On the Effectiveness of Random Weights in Graph Neural Networks. - Thu Bui; Carola-Bibiane Schönlieb; Bruno Ribeiro 001; Beatrice Bevilacqua; Moshe Eliasof (CoRR, 2025)

Generalized Lie Symmetries in Physics-Informed Neural Operators. - Amy Xiang Wang; Zakhar Shumaylov; Peter Zaika; Ferdia Sherry; Carola-Bibiane Schönlieb (CoRR, 2025)

Towards Invariance to Node Identifiers in Graph Neural Networks. - Maya Bechler-Speicher; Moshe Eliasof; Carola-Bibiane Schönlieb; Ran Gilad-Bachrach; Amir Globerson (CoRR, 2025)

A sparse optimization approach to infinite infimal convolution regularization. - Kristian Bredies; Marcello Carioni; Martin Holler; Yury Korolev; Carola-Bibiane Schönlieb (Numerische Mathematik, 2025)

TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation. - Zhongying Deng; Yanqi Cheng; Lihao Liu; Shujun Wang; Rihuan Ke; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (IEEE Trans. Intell. Transp. Syst., 2025)

Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation. - Chun-Wun Cheng; Yining Zhao; Yanqi Cheng; Javier Montoya; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2025)

Enhancing Fourier Neural Operators with Local Spatial Features. - Chaoyu Liu; Davide Murari; Chris J. Budd; Lihao Liu; Carola-Bibiane Schönlieb (CoRR, 2025)

Towards Efficient Training of Graph Neural Networks: A Multiscale Approach. - Eshed Gal; Moshe Eliasof; Carola-Bibiane Schönlieb; Eldad Haber; Eran Treister (CoRR, 2025)

SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events. - 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 (CoRR, 2025)

FLASH: Flexible Learning of Adaptive Sampling from History in Temporal Graph Neural Networks. - Or Feldman; Krishna Sri Ipsit Mantri; Carola-Bibiane Schönlieb; Chaim Baskin; Moshe Eliasof (CoRR, 2025)

RSFR: A Coarse-to-Fine Reconstruction Framework for Diffusion Tensor Cardiac MRI with Semantic-Aware Refinement. - Jiahao Huang; Fanwen Wang; Pedro F. Ferreira; Haosen Zhang; Yinzhe Wu 001; Zhifan Gao; Lei Zhu 003; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Andrew D. Scott; Zohya Khalique; Maria Dwornik; et al. (CoRR, 2025)

Brain Foundation Models with Hypergraph Dynamic Adapter for Brain Disease Analysis. - Zhongying Deng; Haoyu Wang; Ziyan Huang; Lipei Zhang; Angelica I. Avilés-Rivero; Chaoyu Liu; Junjun He; Zoe Kourtzi; Carola-Bibiane Schönlieb (CoRR, 2025)

Approximation theory for 1-Lipschitz ResNets. - Davide Murari; Takashi Furuya; Carola-Bibiane Schönlieb (CoRR, 2025)

Multi-Level Monte Carlo Training of Neural Operators. - James Rowbottom; Stefania Fresca; Pietro Lio; Carola-Bibiane Schönlieb; Nicolas Boullé (CoRR, 2025)

Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling. - Andrea Ceni; Alessio Gravina; Claudio Gallicchio; Davide Bacciu; Carola-Bibiane Schönlieb; Moshe Eliasof (CoRR, 2025)

Deep Spectral Prior. - Yanqi Cheng; Tieyong Zeng; Pietro Lio; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2025)

Smooth Model Compression without Fine-Tuning. - Christina Runkel; Natacha Kuete Meli; Jovita Lukasik; Ander Biguri; Carola-Bibiane Schönlieb; Michael Möller 001 (CoRR, 2025)

Conservation-preserved Fourier Neural Operator through Adaptive Correction. - Chaoyu Liu; Yangming Li; Zhongying Deng; Chris J. Budd; Carola-Bibiane Schönlieb (CoRR, 2025)

Bridging Annotation Gaps: Transferring Labels to Align Object Detection Datasets. - Mikhail Kennerley; Angelica I. Avilés-Rivero; Carola-Bibiane Schönlieb; Robby T. Tan (CoRR, 2025)

Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks. - Ali Hariri; Alvaro Arroyo; Alessio Gravina; Moshe Eliasof; Carola-Bibiane Schönlieb; Davide Bacciu; Kamyar Azizzadenesheli; Xiaowen Dong 001; Pierre Vandergheynst (CoRR, 2025)

Data-driven approaches to inverse problems. - Carola-Bibiane Schönlieb; Zakhar Shumaylov (CoRR, 2025)

PhotIQA: A photoacoustic image data set with image quality ratings. - Anna Breger; Janek Gröhl; Clemens Karner; Thomas R. Else; Ian Selby; Jonathan R. Weir-McCall; Carola-Bibiane Schönlieb (CoRR, 2025)

Neural Networks with Orthogonal Jacobian. - Alex Massucco; Davide Murari; Carola-Bibiane Schönlieb (CoRR, 2025)

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows. - Moshe Eliasof; Eldad Haber; Carola-Bibiane Schönlieb (CoRR, 2025)

Vehicle detection from GSV imagery: Predicting travel behaviour for cycling and motorcycling using Computer Vision. - Kyriaki Kokka; Rahul Goel; Ali Abbas; Kerry A. Nice; Luca Martial; S. M. Labib; Rihuan Ke; Carola-Bibiane Schönlieb; James Woodcock (CoRR, 2025)

Convergent Regularization in Inverse Problems and Linear Plug-and-Play Denoisers. - Andreas Hauptmann; Subhadip Mukherjee; Carola-Bibiane Schönlieb; Ferdia Sherry (Found. Comput. Math., 2025)

Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Linear Inverse Problems. - Junqi Tang; Guixian Xu; Subhadip Mukherjee; Carola-Bibiane Schönlieb (J. Math. Imaging Vis., 2025)