ML Anthology

Cohen, Taco

37 publications

TMLR 2025 Does Equivariance Matter at Scale? Johann Brehmer, Sönke Behrends, Pim De Haan, Taco Cohen
ICML 2025 RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve
ICLR 2025 The KoLMogorov Test: Compression by Code Generation Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen
NeurIPS 2025 UMA: A Family of Universal Models for Atoms Brandon M Wood, Misko Dzamba, Xiang Fu, Meng Gao, Muhammed Shuaibi, Luis Barroso-Luque, Kareem Abdelmaqsoud, Vahe Gharakhanyan, John R. Kitchin, Daniel S. Levine, Kyle Michel, Anuroop Sriram, Taco Cohen, Abhishek Das, Sushree Jagriti Sahoo, Ammar Rizvi, Zachary Ward Ulissi, C. Lawrence Zitnick
ICLR 2025 What Makes Large Language Models Reason in (Multi-Turn) Code Generation? Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin Negrevergne, Gabriel Synnaeve
ICML 2024 CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay Natasha Butt, Blazej Manczak, Auke Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen
ICLRW 2024 CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay Natasha Butt, Blazej Manczak, Auke Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen
TMLR 2024 Deconfounding Imitation Learning with Variational Inference Risto Vuorio, Pim De Haan, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen
NeurIPSW 2024 Does Equivariance Matter at Scale? Johann Brehmer, Sönke Behrends, Pim De Haan, Taco Cohen
AISTATS 2024 Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers Pim Haan, Taco Cohen, Johann Brehmer
ICLRW 2024 Towards Self-Improving Language Models for Code Generation Michaël Defferrard, Corrado Rainone, David W. Zhang, Blazej Manczak, Natasha Butt, Taco Cohen
UAI 2023 BISCUIT: Causal Representation Learning from Binary Interactions Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves
ICLR 2023 Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves
ICLRW 2023 EDGI: Equivariant Diffusion for Planning with Embodied Agents Johann Brehmer, Joey Bose, Pim De Haan, Taco Cohen
NeurIPSW 2023 Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers Pim De Haan, Taco Cohen, Johann Brehmer
NeurIPSW 2023 FoMo Rewards: Can We Cast Foundation Models as Reward Functions? Ekdeep Singh Lubana, Johann Brehmer, Pim De Haan, Taco Cohen
ICMLW 2023 Geometric Algebra Transformers Johann Brehmer, Pim De Haan, Sönke Behrends, Taco Cohen
TMLR 2023 Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set Ties van Rozendaal, Johann Brehmer, Yunfan Zhang, Reza Pourreza, Auke J. Wiggers, Taco Cohen
ICML 2023 On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Lio
ICML 2022 CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Stratis Gavves
ICLRW 2022 CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M Asano, Taco Cohen, Efstratios Gavves
NeurIPSW 2022 Deconfounded Imitation Learning Risto Vuorio, Pim De Haan, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen
ICLR 2022 Efficient Neural Causal Discovery Without Acyclicity Constraints Phillip Lippe, Taco Cohen, Efstratios Gavves
TMLR 2022 Equivariant Mesh Attention Networks Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen
ICLRW 2022 Implicit Neural Video Compression Yunfan Zhang, Ties van Rozendaal, Johann Brehmer, Markus Nagel, Taco Cohen
NeurIPSW 2022 On the Expressive Power of Geometric Graph Neural Networks Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Liò
ICLR 2022 Transformer-Based Transform Coding Yinhao Zhu, Yang Yang, Taco Cohen
ICLRW 2022 Weakly Supervised Causal Representation Learning Johann Brehmer, Pim De Haan, Phillip Lippe, Taco Cohen
ICCV 2021 Extending Neural P-Frame Codecs for B-Frame Coding Reza Pourreza, Taco Cohen
ICLR 2021 Gauge Equivariant Mesh CNNs: Anisotropic Convolutions on Geometric Graphs Pim De Haan, Maurice Weiler, Taco Cohen, Max Welling
ICLR 2021 Overfitting for Fun and Profit: Instance-Adaptive Data Compression Ties van Rozendaal, Iris AM Huijben, Taco Cohen
CVPRW 2020 Adversarial Distortion for Learned Video Compression Vijay Veerabadran, Reza Pourreza, AmirHossein Habibian, Taco Cohen
ICML 2020 Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks Adeel Pervez, Taco Cohen, Efstratios Gavves
ICML 2019 Gauge Equivariant Convolutional Networks and the Icosahedral CNN Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling
ICML 2016 Group Equivariant Convolutional Networks Taco Cohen, Max Welling
ICML 2015 Harmonic Exponential Families on Manifolds Taco Cohen, Max Welling
ICML 2014 Learning the Irreducible Representations of Commutative Lie Groups Taco Cohen, Max Welling