| 2025 | ICLR | The KoLMogorov Test: Compression by Code Generation. | Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen |
| 2025 | ICLR | What Makes Large Language Models Reason in (Multi-Turn) Code Generation? | Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin NXuanjinggrevergne, Gabriel Synnaeve |
| 2025 | ICML | RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning. | Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve |
| 2024 | AISTATS | Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. | Pim de Haan, Taco Cohen, Johann Brehmer |
| 2024 | ICML | CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay. | Natasha Butt, Blazej Manczak, Auke J. Wiggers, Corrado Rainone, David W. Zhang, Michal Defferrard, Taco Cohen |
| 2024 | ICRA | Information-driven Affordance Discovery for Efficient Robotic Manipulation. | Pietro Mazzaglia, Taco Cohen, Daniel Dijkman |
| 2023 | ICLR | Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems. | Phillip Lippe, Sara Magliacane, Sindy Lwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves |
| 2023 | ICML | On the Expressive Power of Geometric Graph Neural Networks. | Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Lio |
| 2023 | UAI | BISCUIT: Causal Representation Learning from Binary Interactions. | Phillip Lippe, Sara Magliacane, Sindy Lwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves |
| 2022 | ICLR | Efficient Neural Causal Discovery without Acyclicity Constraints. | Phillip Lippe, Taco Cohen, Efstratios Gavves |
| 2022 | ICLR | Transformer-based Transform Coding. | Yinhao Zhu, Yang Yang, Taco Cohen |
| 2022 | ICML | CITRIS: Causal Identifiability from Temporal Intervened Sequences. | Phillip Lippe, Sara Magliacane, Sindy Lwe, Yuki M. Asano, Taco Cohen, Stratis Gavves |
| 2021 | ICCV | Extending Neural P-frame Codecs for B-frame Coding. | Reza Pourreza, Taco Cohen |
| 2021 | ICLR | Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. | Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling |
| 2021 | ICLR | Overfitting for Fun and Profit: Instance-Adaptive Data Compression. | Ties van Rozendaal, Iris A. M. Huijben, Taco Cohen |
| 2020 | CVPR | Adversarial Distortion for Learned Video Compression. | Vijay Veerabadran, Reza Pourreza, AmirHossein Habibian, Taco Cohen |
| 2020 | ICML | Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks. | Adeel Pervez, Taco Cohen, Efstratios Gavves |
| 2020 | MMSP | Parallelized Rate-Distortion Optimized Quantization Using Deep Learning. | Dana Kianfar, Auke J. Wiggers, Amir Said, Reza Pourreza, Taco Cohen |
| 2019 | ICCV | Video Compression With Rate-Distortion Autoencoders. | AmirHossein Habibian, Ties van Rozendaal, Jakub M. Tomczak, Taco Cohen |
| 2019 | ICML | Gauge Equivariant Convolutional Networks and the Icosahedral CNN. | Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling |
| 2018 | MICCAI | Rotation Equivariant CNNs for Digital Pathology. | Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling |
| 2016 | ICML | Group Equivariant Convolutional Networks. | Taco Cohen, Max Welling |
| 2015 | ICML | Harmonic Exponential Families on Manifolds. | Taco Cohen, Max Welling |
| 2014 | ICML | Learning the Irreducible Representations of Commutative Lie Groups. | Taco Cohen, Max Welling |