Schönlieb, Carola-Bibiane

53 publications

NeurIPS 2025 Approximation Theory for 1-Lipschitz ResNets Davide Murari, Takashi Furuya, Carola-Bibiane Schönlieb

ICLRW 2025 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

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

NeurIPS 2025 D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction Lipei Zhang, Rui Sun, Zhongying Deng, Yanqi Cheng, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

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

ICLR 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

ICML 2025 G-Adaptivity: Optimised Graph-Based Mesh Relocation for Finite Element Methods James Rowbottom, Georg Maierhofer, Teo Deveney, Eike Hermann Müller, Alberto Paganini, Katharina Schratz, Pietro Lio, Carola-Bibiane Schönlieb, Chris Budd

ICML 2025 Graph Adaptive Autoregressive Moving Average Models Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

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

ICLR 2025 Lie Algebra Canonicalization: Equivariant Neural Operators Under Arbitrary Lie Groups Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb

TMLR 2025 Neural Varifolds: An Aggregate Representation for Quantifying the Geometry of Point Clouds Juheon Lee, Xiaohao Cai, Carola-Bibiane Schönlieb, Simon Masnou

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

NeurIPS 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, Xiaowen Dong, Kamyar Azizzadenesheli, Pierre Vandergheynst

ICML 2025 Score-Based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry Using Anisotropic Flows Willem Diepeveen, Georgios Batzolis, Zakhar Shumaylov, Carola-Bibiane Schönlieb

TMLR 2025 Towards Efficient Training of Graph Neural Networks: A Multiscale Approach Eshed Gal, Moshe Eliasof, Carola-Bibiane Schönlieb, Ivan Kyrchei, Eldad Haber, Eran Treister

TMLR 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

CVPRW 2025 Training Data Reconstruction: Privacy Due to Uncertainty? Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller

TMLR 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, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

NeurIPSW 2024 Adaptive Neighborhoods in Contrastive Regression Learning for Brain Age Prediction Jakob Träuble, Lucy V Hiscox, Curtis Johnson, Carola-Bibiane Schönlieb, Gabriele S Kaminski Schierle, Angelica I Aviles-Rivero

TMLR 2024 Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

TMLR 2024 Continuous U-Net: Faster, Greater and Noiseless Chun-Wun Cheng, Christina Runkel, Lihao Liu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

TMLR 2024 Contrastive Learning with Adaptive Neighborhoods for Brain Age Prediction on 3D Stiffness Maps Jakob Träuble, Lucy V Hiscox, Curtis Johnson, Carola-Bibiane Schönlieb, Gabriele S Kaminski Schierle, Angelica I Aviles-Rivero

ICLRW 2024 Data-Driven Higher Order Differential Equations Inspired Graph Neural Networks Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb

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

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

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

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

NeurIPSW 2024 Hamiltonian Matching for Symplectic Neural Integrators Priscilla Canizares, Davide Murari, Carola-Bibiane Schönlieb, Ferdia Sherry, Zakhar Shumaylov

TMLR 2024 NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning Zhongying Deng, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

NeurIPSW 2024 Random Propagations in GNNs Thu Bui, Anugunj Naman, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof

NeurIPSW 2024 Rethinking Fine-Tuning Through Geometric Perspective Krishna Sri Ipsit Mantri, Moshe Eliasof, Carola-Bibiane Schönlieb, Bruno Ribeiro

TMLR 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 Aviles-Rivero

TMLR 2024 The Missing U for Efficient Diffusion Models Sergio Calvo Ordoñez, Chun-Wun Cheng, Jiahao Huang, Lipei Zhang, Guang Yang, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

NeurIPSW 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, Haggai Maron

TMLR 2024 Unsupervised Training of Convex Regularizers Using Maximum Likelihood Estimation Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb

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

JMLR 2023 A Continuous-Time Stochastic Gradient Descent Method for Continuous Data Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb

ICCVW 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

NeurIPSW 2023 Provably Convergent Data-Driven Convex-Nonconvex Regularization Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee, Carola-Bibiane Schönlieb

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

ICLRW 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 Aviles-Rivero

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

JMLR 2022 On Biased Stochastic Gradient Estimation Derek Driggs, Jingwei Liang, Carola-Bibiane Schönlieb

ECCV 2022 Rethinking Video Rain Streak Removal: A New Synthesis Model and a Deraining Network with Video Rain Prior Shuai Wang, Lei Zhu, Huazhu Fu, Jing Qin, Carola-Bibiane Schönlieb, Wei Feng, Song Wang

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

NeurIPSW 2022 Structure Preserving Neural Networks Based on ODEs Davide Murari, Elena Celledoni, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry

JMLR 2022 TFPnP: Tuning-Free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Hua Huang, Carola-Bibiane Schönlieb

NeurIPS 2021 End-to-End Reconstruction Meets Data-Driven Regularization for Inverse Problems Subhadip Mukherjee, Marcello Carioni, Ozan Öktem, Carola-Bibiane Schönlieb

NeurIPSW 2021 Invertible Learned Primal-Dual Jevgenija Rudzusika, Buda Bajic, Ozan Öktem, Carola-Bibiane Schönlieb, Christian Etmann

NeurIPSW 2021 Learning Convex Regularizers Satisfying the Variational Source Condition for Inverse Problems Subhadip Mukherjee, Carola-Bibiane Schönlieb, Martin Burger

ECCVW 2020 Learning to Segment Microscopy Images with Lazy Labels Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis, Peter Schütz, Carola-Bibiane Schönlieb

ICML 2020 Tuning-Free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang

NeurIPS 2018 Adversarial Regularizers in Inverse Problems Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb