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ORCIDCarola-Bibiane Schönlieb
Carola-Bibiane Schoenlieb – Carola Schönlieb – Carola B. Schönlieb
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- affiliation: University of Cambridge, UK
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2020 – today
- 2025
[j95]Xiaodan Xing, Chunling Tang, Siofra Murdoch, Giorgos Papanastasiou, Yunzhe Guo, Xianglu Xiao, Jan Oscar Cross-Zamirski, Carola-Bibiane Schönlieb, Kristina Xiao Liang, Zhangming Niu, Evandro Fei Fang, Yinhai Wang, Guang Yang
:
Artificial immunofluorescence in a flash: Rapid synthetic imaging from brightfield through residual diffusion. Neurocomputing 612: 128715 (2025)- [j94]Jiahao Huang, Liutao Yang, Fanwen Wang, Yinzhe Wu, Yang Nan, Weiwen Wu, Chengyan Wang, Kuangyu Shi, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang:
Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba. Medical Image Anal. 99: 103334 (2025) - 2024
- [j93]Xiaodan Xing, Siofra Murdoch, Chunling Tang, Giorgos Papanastasiou, Jan Oscar Cross-Zamirski, Yunzhe Guo, Xianglu Xiao, Carola-Bibiane Schönlieb, Yinhai Wang, Guang Yang:
Can generative AI replace immunofluorescent staining processes? A comparison study of synthetically generated cellpainting images from brightfield. Comput. Biol. Medicine 182: 109102 (2024) - [j92]Yifan Li, Chao Li, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen:
Multi-objective Bayesian optimization with enhanced features for adaptively improved glioblastoma partitioning and survival prediction. Comput. Medical Imaging Graph. 116: 102420 (2024) - [j91]Simone Saitta, Marcello Carioni, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Alberto Redaelli:
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI. Comput. Methods Programs Biomed. 246: 108057 (2024) - [j90]Antonin Chambolle, Claire Delplancke, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang:
Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes. J. Math. Imaging Vis. 66(3): 294-313 (2024) - [j89]Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb:
The curious case of the test set AUROC. Nat. Mac. Intell. 6(4): 373-376 (2024) - [j88]Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb:
Publisher Correction: The curious case of the test set AUROC. Nat. Mac. Intell. 6(4): 494 (2024) - [j87]Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts:
Recent methodological advances in federated learning for healthcare. Patterns 5(6): 101006 (2024) - [j86]Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis:
A linear transportation Lp distance for pattern recognition. Pattern Recognit. 147: 110080 (2024) - [j85]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Provably Convergent Plug-and-Play Quasi-Newton Methods. SIAM J. Imaging Sci. 17(2): 785-819 (2024) - [j84]Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang:
NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems. SIAM J. Imaging Sci. 17(2): 820-860 (2024) - [j83]Matthias J. Ehrhardt, Lorenz Kuger, Carola-Bibiane Schönlieb:
Proximal Langevin Sampling with Inexact Proximal Mapping. SIAM J. Imaging Sci. 17(3): 1729-1760 (2024) - [j82]Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang:
Practical Acceleration of the Condat-Vũ Algorithm. SIAM J. Imaging Sci. 17(4): 2076-2109 (2024) - [j81]Sergio Calvo-Ordoñez, Chun-Wun Cheng, Jiahao Huang, Lipei Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
The Missing U for Efficient Diffusion Models. Trans. Mach. Learn. Res. 2024 (2024) - [j80]Chun-Wun Cheng, Christina Runkel, Lihao Liu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Continuous U-Net: Faster, Greater and Noiseless. Trans. Mach. Learn. Res. 2024 (2024) - [j79]Zhongying Deng, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning. Trans. Mach. Learn. Res. 2024 (2024) - [j78]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration. Trans. Mach. Learn. Res. 2024 (2024) - [j77]Philip Sellars, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb:
LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semisupervised Classification. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5306-5318 (2024) - [c64]Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb:
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. AISTATS 2024: 1792-1800 - [c63]Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb:
Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach. ECAI 2024: 1607-1614 - [c62]Subhadip Mukherjee, Sören Dittmer, Zakhar Shumaylov, Sebastian Lunz, Ozan Öktem, Carola B. Schönlieb:
Data-Driven Convex Regularizers for Inverse Problems. ICASSP 2024: 13386-13390 - [c61]Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations. ICML 2024 - [c60]Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee, Carola-Bibiane Schönlieb:
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation. ICML 2024 - [c59]Jan Stanczuk, Georgios Batzolis, Teo Deveney, Carola-Bibiane Schönlieb:
Diffusion Models Encode the Intrinsic Dimension of Data Manifolds. ICML 2024 - [c58]Pengze Li, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Optimised Propainter for Video Diminished Reality Inpainting. ISBI 2024: 1-5 - [c57]Lipei Zhang, Yanqi Cheng, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation. MICCAI (12) 2024: 3-13 - [c56]Ruodan Yan, Carola-Bibiane Schönlieb, Chao Li:
Spatiotemporal Graph Neural Network Modelling Perfusion MRI. MICCAI (2) 2024: 411-421 - [c55]Christina Runkel, Ander Biguri, Carola-Bibiane Schönlieb:
Continuous Learned Primal Dual. MLSP 2024: 1-6 - [c54]Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, Angelica E. Avilés-Rivero:
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. ACM Multimedia 2024: 1265-1273 - [i194]Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb:
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. CoRR abs/2401.11074 (2024) - [i193]Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee, Carola-Bibiane Schönlieb:
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation. CoRR abs/2402.01052 (2024) - [i192]Andrey Bryutkin, Jiahao Huang, Zhongying Deng, Guang Yang, Carola-Bibiane Schönlieb, Angelica E. Avilés-Rivero:
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations. CoRR abs/2402.03541 (2024) - [i191]Jiahao Huang, Liutao Yang, Fanwen Wang, Yinzhe Wu, Yang Nan, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang:
MambaMIR: An Arbitrary-Masked Mamba for Joint Medical Image Reconstruction and Uncertainty Estimation. CoRR abs/2402.18451 (2024) - [i190]Lipei Zhang, Yanqi Cheng, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation. CoRR abs/2403.09136 (2024) - [i189]Angelica I. Avilés-Rivero, Chun-Wun Cheng, Zhongying Deng, Zoe Kourtzi, Carola-Bibiane Schönlieb:
Bilevel Hypergraph Networks for Multi-Modal Alzheimer's Diagnosis. CoRR abs/2403.12719 (2024) - [i188]Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. CoRR abs/2404.05445 (2024) - [i187]Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron:
GRANOLA: Adaptive Normalization for Graph Neural Networks. CoRR abs/2404.13344 (2024) - [i186]Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb:
Tackling Graph Oversquashing by Global and Local Non-Dissipativity. CoRR abs/2405.01009 (2024) - [i185]Christina Runkel, Ander Biguri, Carola-Bibiane Schönlieb:
Continuous Learned Primal Dual. CoRR abs/2405.02478 (2024) - [i184]Xiaodan Xing, Fadong Shi, Jiahao Huang, Yinzhe Wu, Yang Nan, Sheng Zhang, Yingying Fang, Mike Roberts, Carola-Bibiane Schönlieb, Javier Del Ser, Guang Yang:
When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI. CoRR abs/2405.09597 (2024) - [i183]Jiahao Huang, Liutao Yang, Fanwen Wang, Yang Nan, Weiwen Wu, Chengyan Wang, Kuangyu Shi, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang:
Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba. CoRR abs/2405.17659 (2024) - [i182]Fan Zhang, Carlos Esteve-Yagüe, Sören Dittmer, Carola-Bibiane Schönlieb, Michael Roberts:
FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimization. CoRR abs/2405.19000 (2024) - [i181]Anna Breger, Ander Biguri, Malena Sabaté Landman, Ian Selby, Nicole Amberg, Elisabeth Brunner, Janek Gröhl, Sepideh Hatamikia, Clemens Karner, Lipeng Ning, Sören Dittmer, Michael Roberts, AIX-COVNET Collaboration, Carola-Bibiane Schönlieb:
A study of why we need to reassess full reference image quality assessment with medical images. CoRR abs/2405.19097 (2024) - [i180]Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb:
A study on the adequacy of common IQA measures for medical images. CoRR abs/2405.19224 (2024) - [i179]Pengze Li, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Optimised ProPainter for Video Diminished Reality Inpainting. CoRR abs/2406.02287 (2024) - [i178]Chaoyan Huang, Zhongming Wu, Yanqi Cheng, Tieyong Zeng, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems. CoRR abs/2406.02458 (2024) - [i177]Ruodan Yan, Carola-Bibiane Schönlieb, Chao Li:
Spatiotemporal Graph Neural Network Modelling Perfusion MRI. CoRR abs/2406.06434 (2024) - [i176]Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof:
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. CoRR abs/2407.02013 (2024) - [i175]James Rowbottom, Georg Maierhofer, Teo Deveney, Katharina Schratz, Pietro Liò, Carola-Bibiane Schönlieb, Chris J. Budd:
G-Adaptive mesh refinement - leveraging graph neural networks and differentiable finite element solvers. CoRR abs/2407.04516 (2024) - [i174]Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, Simon Masnou:
Neural varifolds: an aggregate representation for quantifying the geometry of point clouds. CoRR abs/2407.04844 (2024) - [i173]Yi Zhang, Chun-Wun Cheng, Ke Yu, Zhihai He, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning. CoRR abs/2407.08672 (2024) - [i172]Jakob Träuble, Lucy V. Hiscox, Curtis L. Johnson, Carola-Bibiane Schönlieb, Gabriele Kaminski Schierle, Angelica I. Avilés-Rivero:
Contrastive Learning with Dynamic Localized Repulsion for Brain Age Prediction on 3D Stiffness Maps. CoRR abs/2408.00527 (2024) - [i171]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. CoRR abs/2408.06996 (2024) - [i170]Maximilian B. Kiss, Ander Biguri, Carola-Bibiane Schönlieb, Kees Joost Batenburg, Felix Lucka:
Learned denoising with simulated and experimental low-dose CT data. CoRR abs/2408.08115 (2024) - [i169]Simon Deltadahl, Julian D. Gilbey, Christine van Laer, Nancy Boeckx, Mathie Leers, Tanya Freeman, Laura Aiken, Timothy Farren, Matthew Smith, Mohamad Zeina, BloodCounts Consortium, Concetta Piazzese, Joseph Taylor, Nicholas S. Gleadall, Carola-Bibiane Schönlieb, Suthesh Sivapalaratnam, Michael Roberts, Parashkev Nachev:
Deep Generative Classification of Blood Cell Morphology. CoRR abs/2408.08982 (2024) - [i168]Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber:
Learning Regularization for Graph Inverse Problems. CoRR abs/2408.10436 (2024) - [i167]Tobias Wolf, Derek Driggs, Kostas Papafitsoros, Elena Resmerita, Carola-Bibiane Schönlieb:
Nested Bregman Iterations for Decomposition Problems. CoRR abs/2409.01097 (2024) - [i166]Liutao Yang, Jiahao Huang, Yingying Fang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Daoqiang Zhang, Guang Yang:
Learning Task-Specific Sampling Strategy for Sparse-View CT Reconstruction. CoRR abs/2409.01544 (2024) - [i165]Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann:
Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling. CoRR abs/2409.05804 (2024) - [i164]Yangming Li, Chieh-Hsin Lai, Carola-Bibiane Schönlieb, Yuki Mitsufuji, Stefano Ermon:
Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space. CoRR abs/2410.01796 (2024) - [i163]Willem Diepeveen, Georgios Batzolis, Zakhar Shumaylov, Carola-Bibiane Schönlieb:
Score-based pullback Riemannian geometry. CoRR abs/2410.01950 (2024) - [i162]Chun-Wun Cheng, Jiahao Huang, Yi Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs. CoRR abs/2410.02113 (2024) - [i161]Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb:
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. CoRR abs/2410.02698 (2024) - [i160]Friso de Kruiff, Erik Bekkers, Ozan Öktem, Carola-Bibiane Schönlieb, Willem Diepeveen:
Pullback Flow Matching on Data Manifolds. CoRR abs/2410.04543 (2024) - [i159]Priscilla Canizares, Davide Murari, Carola-Bibiane Schönlieb, Ferdia Sherry, Zakhar Shumaylov:
Hamiltonian Matching for Symplectic Neural Integrators. CoRR abs/2410.18262 (2024) - [i158]Clemens Karner, Janek Gröhl, Ian Selby, Judith Babar, Jake Beckford, Thomas R. Else, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, James H. F. Rudd, Carola-Bibiane Schönlieb, Jonathan R. Weir-McCall, Anna Breger:
Parameter choices in HaarPSI for IQA with medical images. CoRR abs/2410.24098 (2024) - 2023
- [j76]Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang:
Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation. J. Digit. Imaging 36(2): 739-752 (2023) - [j75]Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb:
A Continuous-time Stochastic Gradient Descent Method for Continuous Data. J. Mach. Learn. Res. 24: 274:1-274:48 (2023) - [j74]Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb:
Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. 5(7): 681-686 (2023) - [j73]Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto, Carola-Bibiane Schönlieb:
Joint Reconstruction-Segmentation on Graphs. SIAM J. Imaging Sci. 16(2): 911-947 (2023) - [j72]Willem Diepeveen, Jan Lellmann, Ozan Öktem, Carola-Bibiane Schönlieb:
Regularizing Orientation Estimation in Cryogenic Electron Microscopy Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds. SIAM J. Imaging Sci. 16(3): 1440-1490 (2023) - [j71]Elena Celledoni, Davide Murari, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry:
Dynamical Systems-Based Neural Networks. SIAM J. Sci. Comput. 45(3): 3071-3094 (2023) - [j70]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Data-Driven Mirror Descent with Input-Convex Neural Networks. SIAM J. Math. Data Sci. 5(2): 558-587 (2023) - [j69]Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry, Julián Tachella:
Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning. IEEE Signal Process. Mag. 40(1): 134-147 (2023) - [j68]Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb:
Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications. IEEE Signal Process. Mag. 40(1): 164-182 (2023) - [j67]Huazhu Fu, Yitian Zhao, Pew-Thian Yap, Carola-Bibiane Schönlieb, Alejandro F. Frangi:
Guest Editorial Special Issue on Geometric Deep Learning in Medical Imaging. IEEE Trans. Medical Imaging 42(2): 332-335 (2023) - [j66]Yiran Wei, Xi Chen, Lei Zhu, Lipei Zhang, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li:
Multi-Modal Learning for Predicting the Genotype of Glioma. IEEE Trans. Medical Imaging 42(11): 3167-3178 (2023) - [j65]Lei Zhu, Xiaoqiang Wang, Ping Li, Xin Yang, Qing Zhang, Weiming Wang, Carola-Bibiane Schönlieb, C. L. Philip Chen:
S $^3$ Net: Self-Supervised Self-Ensembling Network for Semi-Supervised RGB-D Salient Object Detection. IEEE Trans. Multim. 25: 676-689 (2023) - [c53]Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
SCOTCH and SODA: A Transformer Video Shadow Detection Framework. CVPR 2023: 10449-10458 - [c52]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Andreas Hauptmann, Carola-Bibiane Schönlieb:
Robust Data-Driven Accelerated Mirror Descent. ICASSP 2023: 1-5 - [c51]Jan Oscar Cross-Zamirski, Praveen Anand, Guy B. Williams, Elizabeth Mouchet, Yinhai Wang, Carola-Bibiane Schönlieb:
Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels. ICCV (Workshops) 2023: 3802-3811 - [c50]Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang:
ViGU: Vision GNN U-Net for fast MRI. ISBI 2023: 1-5 - [c49]Chao Li, Wenjian Huang, Xi Chen, Yiran Wei, Lipei Zhang, Jianguo Zhang, Stephen J. Price, Carola-Bibiane Schönlieb:
Expectation-Maximization Regularised Deep Learning for Tumour Segmentation. ISBI 2023: 1-5 - [c48]Yiran Wei, Xi Chen, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li:
Predicting Conversion of Mild Cognitive Impairment to Alzheimer's Disease by Modelling Healthy Ageing Trajectories. ISBI 2023: 1-5 - [c47]Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang:
CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI? MICCAI (10) 2023: 3-12 - [c46]Yifan Li, Chao Li, Yiran Wei, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen:
G-CNN: Adaptive Geometric Convolutional Neural Networks for MRI-Based Skull Stripping. CMMCA@MICCAI 2023: 21-30 - [c45]Yijun Yang, Huazhu Fu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Lei Zhu:
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification. MICCAI (6) 2023: 95-105 - [c44]Christina Runkel, Michael Möller, Carola-Bibiane Schönlieb, Christian Etmann:
Learning Posterior Distributions in Underdetermined Inverse Problems. SSVM 2023: 187-209 - [c43]Yanqi Cheng, Lihao Liu, Shujun Wang, Yueming Jin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition Through the Lens of Robustness. TML4H 2023: 177-189 - [i157]Chun-Wun Cheng, Christina Runkel, Lihao Liu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Continuous U-Net: Faster, Greater and Noiseless. CoRR abs/2302.00626 (2023) - [i156]Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz, Carola-Bibiane Schönlieb:
Can Physics-Informed Neural Networks beat the Finite Element Method? CoRR abs/2302.04107 (2023) - [i155]Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang:
ViGU: Vision GNN U-Net for Fast MRI. CoRR abs/2302.10273 (2023) - [i154]Simone Saitta, Marcello Carioni, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Alberto Redaelli:
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI. CoRR abs/2302.12835 (2023) - [i153]Tamara G. Grossmann, Carola-Bibiane Schönlieb, Orietta Da Rold:
Hidden Knowledge: Mathematical Methods for the Extraction of the Fingerprint of Medieval Paper from Digital Images. CoRR abs/2303.03794 (2023) - [i152]Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Martin Weigert, Uwe Schmidt, Wenhua Zhang, Jun Zhang, Sen Yang, Jinxi Xiang, Xiyue Wang, Josef Lorenz Rumberger, Elias Baumann, Peter Hirsch, Lihao Liu, Chenyang Hong, Angelica I. Avilés-Rivero, Ayushi Jain, Heeyoung Ahn, Yiyu Hong, Hussam Azzuni, Min Xu, Mohammad Yaqub, Marie-Claire Blache, Benoît Piégu, Bertrand Vernay, Tim Scherr, Moritz Böhland, Katharina Löffler, Jiachen Li, Weiqin Ying, Chixin Wang, Dagmar Kainmueller, Carola-Bibiane Schönlieb, Shuolin Liu, Dhairya Talsania, Yughender Meda, Prakash Mishra, Muhammad Ridzuan, Oliver Neumann, Marcel P. Schilling, Markus Reischl, Ralf Mikut, Banban Huang, Hsiang-Chin Chien, Ching-Ping Wang, Chia-Yen Lee, Hong-Kun Lin, Zaiyi Liu, Xipeng Pan, Chu Han, Jijun Cheng, Muhammad Dawood, Srijay Deshpande, Raja Muhammad Saad Bashir, Adam Shephard, Pedro Costa, João D. Nunes, Aurélio Campilho, Jaime S. Cardoso, Hrishikesh P. S, Densen Puthussery, Devika R. G, Jiji C V, Ye Zhang, Zijie Fang, Zhifan Lin, Yongbing Zhang, Chunhui Lin, Liukun Zhang, Lijian Mao, Min Wu, Thi Tuong Vi Vo, Soo-Hyung Kim, Taebum Lee, Satoshi Kondo, Satoshi Kasai, Pranay Dumbhare, Vedant Phuse, Yash Dubey, Ankush Jamthikar, Trinh Thi Le Vuong, Jin Tae Kwak, Dorsa Ziaei, Hyun Jung, Tianyi Miao, David R. J. Snead, Shan-E-Ahmed Raza, Fayyaz Minhas, Nasir M. Rajpoot:
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting. CoRR abs/2303.06274 (2023) - [i151]Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb:
Provably Convergent Plug-and-Play Quasi-Newton Methods. CoRR abs/2303.07271 (2023) - [i150]Jing Zou, Noémie Debroux, Lihao Liu, Jing Qin, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation. CoRR abs/2303.08113 (2023) - [i149]Jan Oscar Cross-Zamirski, Praveen Anand, Guy B. Williams, Elizabeth Mouchet, Yinhai Wang, Carola-Bibiane Schönlieb:
Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels. CoRR abs/2303.08863 (2023) - [i148]Shujun Wang, Angelica I. Avilés-Rivero, Zoe Kourtzi, Carola-Bibiane Schönlieb:
HGIB: Prognosis for Alzheimer's Disease via Hypergraph Information Bottleneck. CoRR abs/2303.10390 (2023) - [i147]Yijun Yang, Huazhu Fu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Lei Zhu:
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification. CoRR abs/2303.10610 (2023) - [i146]Jiahao Huang, Pedro F. Ferreira, Lichao Wang, Yinzhe Wu, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Ramyah Rajakulasingam, Ranil De Silva, Dudley J. Pennell, Sonia Nielles-Vallespin, Guang Yang:
Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study. CoRR abs/2304.00996 (2023) - [i145]Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang:
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems. CoRR abs/2304.08342 (2023) - [i144]Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb:
Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior. CoRR abs/2304.12141 (2023) - [i143]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:
Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data. CoRR abs/2306.09177 (2023) - [i142]Jiahao Huang, Angelica I. Avilés-Rivero, Carola-Bibiane Schönlieb, Guang Yang:
CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI? CoRR abs/2306.14350 (2023) - [i141]Ferdia Sherry, Elena Celledoni, Matthias J. Ehrhardt, Davide Murari, Brynjulf Owren, Carola-Bibiane Schönlieb:
Designing Stable Neural Networks using Convex Analysis and ODEs. CoRR abs/2306.17332 (2023) - [i140]Matthias J. Ehrhardt, Lorenz Kuger, Carola-Bibiane Schönlieb:
Proximal Langevin Sampling With Inexact Proximal Mapping. CoRR abs/2306.17737 (2023) - [i139]Chaoyu Liu, Zhonghua Qiao, Chao Li, Carola-Bibiane Schönlieb:
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks. CoRR abs/2307.07344 (2023) - [i138]