Taco Cohen - RankMe

71 papers A* 20A 2C 1Journal 46Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula. CoRR Cansu Sancaktar, David W. Zhang, Gabriel Synnaeve, Taco Cohen
2025	J	`jnl`	CWM: An Open-Weights LLM for Research on Code Generation with World Models. CoRR FAIR CodeGen team, Jade Copet, Quentin Carbonneaux, Gal Cohen, Jonas Gehring, Jacob Kahn, Jannik Kossen, Felix Kreuk, Emily McMilin, Michel Meyer, Yuxiang Wei, David Zhang, Kunhao Zheng, Jordi Armengol-Estapé, Pedram Bashiri, Maximilian Beck, Pierre Chambon, Abhishek Charnalia, Chris Cummins, Juliette Decugis, Zacharias V. Fisches, François Fleuret, Fabian Gloeckle, Alex Gu, Michael Hassid, Daniel Haziza, Badr Youbi Idrissi, Christian Keller, Rahul Kindi, Hugh Leather, Gallil Maimon, Aram H. Markosyan, Francisco Massa, Pierre-Emmanuel Mazaré, Vegard Mella, Naila Murray, Keyur Muzumdar, Peter W. O'Hearn, Matteo Pagliardini, Dmitrii Pedchenko, Tal Remez, Volker Seeker, Marco Selvi, Oren Sultan, Sida Wang, Luca Wehrstedt, Ori Yoran, Lingming Zhang, Taco Cohen, Yossi Adi, Gabriel Synnaeve
2025	J	`jnl`	Does equivariance matter at scale? Trans. Mach. Learn. Res. Johann Brehmer, Sönke Behrends, Pim de Haan, Taco Cohen
2025	J	`jnl`	RL-finetuning LLMs from on- and off-policy data with a single algorithm. CoRR Yunhao Tang, Taco Cohen, David W. Zhang, Michal Valko, Rémi Munos
2025	A*	`conf`	RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning. ICML Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve
2025	J	`jnl`	Soft Policy Optimization: Online Off-Policy RL for Sequence Models. CoRR Taco Cohen, David W. Zhang, Kunhao Zheng, Yunhao Tang, Rémi Munos, Gabriel Synnaeve
2025	A*	`conf`	The KoLMogorov Test: Compression by Code Generation. ICLR Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen
2025	J	`jnl`	The KoLMogorov Test: Compression by Code Generation. CoRR Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen
2025	J	`jnl`	UMA: A Family of Universal Models for Atoms. CoRR 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, Ammar Rizvi, Sushree Jagriti Sahoo, Zachary W. Ulissi, C. Lawrence Zitnick
2025	J	`jnl`	What Does It Take to Be a Good AI Research Agent? Studying the Role of Ideation Diversity. CoRR Alexis Audran-Reiss, Jordi Armengol-Estapé, Karen Hambardzumyan, Amar Budhiraja, Martin Josifoski, Edan Toledo, Rishi Hazra, Despoina Magka, Michael Shvartsman, Parth Pathak, Justine T. Kao, Lucia Cipolina-Kun, Bhavul Gauri, Jean-Christophe Gagnon-Audet, Emanuel Tewolde, Jenny Zhang, Taco Cohen, Yossi Adi, Tatiana Shavrina, Yoram Bachrach
2025	A*	`conf`	What Makes Large Language Models Reason in (Multi-Turn) Code Generation? ICLR Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin NéXuanjinggrevergne, Gabriel Synnaeve
2024	A*	`conf`	CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay. ICML Natasha Butt, Blazej Manczak, Auke J. Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen
2024	J	`jnl`	CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay. CoRR Natasha Butt, Blazej Manczak, Auke J. Wiggers, Corrado Rainone, David W. Zhang, Michaël Defferrard, Taco Cohen
2024	J	`jnl`	Deconfounding Imitation Learning with Variational Inference. Trans. Mach. Learn. Res. Risto Vuorio, Pim de Haan, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen
2024	J	`jnl`	Does equivariance matter at scale? CoRR Johann Brehmer, Sönke Behrends, Pim de Haan, Taco Cohen
2024	A	`conf`	Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. AISTATS Pim de Haan, Taco Cohen, Johann Brehmer
2024	A*	`conf`	Information-driven Affordance Discovery for Efficient Robotic Manipulation. ICRA Pietro Mazzaglia, Taco Cohen, Daniel Dijkman
2024	J	`jnl`	Information-driven Affordance Discovery for Efficient Robotic Manipulation. CoRR Pietro Mazzaglia, Taco Cohen, Daniel Dijkman
2024	J	`jnl`	RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning. CoRR Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve
2024	J	`jnl`	What Makes Large Language Models Reason in (Multi-Turn) Code Generation? CoRR Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin Négrevergne, Gabriel Synnaeve
2023	J	`jnl`	A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
2023	A	`conf`	BISCUIT: Causal Representation Learning from Binary Interactions. UAI Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
2023	J	`jnl`	BISCUIT: Causal Representation Learning from Binary Interactions. CoRR Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
2023	A*	`conf`	Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems. ICLR Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
2023	J	`jnl`	EDGI: Equivariant Diffusion for Planning with Embodied Agents. CoRR Johann Brehmer, Joey Bose, Pim de Haan, Taco Cohen
2023	J	`jnl`	Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers. CoRR Pim de Haan, Taco Cohen, Johann Brehmer
2023	J	`jnl`	FoMo Rewards: Can we cast foundation models as reward functions? CoRR Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan, Taco Cohen
2023	J	`jnl`	Geometric Algebra Transformers. CoRR Johann Brehmer, Pim de Haan, Sönke Behrends, Taco Cohen
2023	J	`jnl`	Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set. Trans. Mach. Learn. Res. Ties van Rozendaal, Johann Brehmer, Yunfan Zhang, Reza Pourreza, Auke J. Wiggers, Taco Cohen
2023	A*	`conf`	On the Expressive Power of Geometric Graph Neural Networks. ICML Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Lio
2023	J	`jnl`	On the Expressive Power of Geometric Graph Neural Networks. CoRR Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Liò
2023	J	`jnl`	Uncertainty-driven Affordance Discovery for Efficient Robotics Manipulation. CoRR Pietro Mazzaglia, Taco Cohen, Daniel Dijkman
2022	J	`jnl`	A PAC-Bayesian Generalization Bound for Equivariant Networks. CoRR Arash Behboodi, Gabriele Cesa, Taco Cohen
2022	A*	`conf`	CITRIS: Causal Identifiability from Temporal Intervened Sequences. ICML Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Stratis Gavves
2022	J	`jnl`	CITRIS: Causal Identifiability from Temporal Intervened Sequences. CoRR Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
2022	J	`jnl`	Deconfounded Imitation Learning. CoRR Risto Vuorio, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen, Pim de Haan
2022	A*	`conf`	Efficient Neural Causal Discovery without Acyclicity Constraints. ICLR Phillip Lippe, Taco Cohen, Efstratios Gavves
2022	J	`jnl`	Equivariant Mesh Attention Networks. CoRR Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen
2022	J	`jnl`	Equivariant Mesh Attention Networks. Trans. Mach. Learn. Res. Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen
2022	J	`jnl`	Guest Editorial: Non-Euclidean Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori
2022	J	`jnl`	Towards a Grounded Theory of Causation for Embodied AI. CoRR Taco Cohen
2022	A*	`conf`	Transformer-based Transform Coding. ICLR Yinhao Zhu, Yang Yang, Taco Cohen
2022	J	`jnl`	Weakly supervised causal representation learning. CoRR Johann Brehmer, Pim de Haan, Phillip Lippe, Taco Cohen
2022	J	`jnl`	iCITRIS: Causal Representation Learning for Instantaneous Temporal Effects. CoRR Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves
2021	J	`jnl`	Efficient Neural Causal Discovery without Acyclicity Constraints. CoRR Phillip Lippe, Taco Cohen, Efstratios Gavves
2021	A*	`conf`	Extending Neural P-frame Codecs for B-frame Coding. ICCV Reza Pourreza, Taco Cohen
2021	A*	`conf`	Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. ICLR Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
2021	J	`jnl`	Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges. CoRR Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Velickovic
2021	J	`jnl`	Implicit Neural Video Compression. CoRR Yunfan Zhang, Ties van Rozendaal, Johann Brehmer, Markus Nagel, Taco Cohen
2021	A*	`conf`	Overfitting for Fun and Profit: Instance-Adaptive Data Compression. ICLR Ties van Rozendaal, Iris A. M. Huijben, Taco Cohen
2020	—	`conf`	Adversarial Distortion for Learned Video Compression. CVPR Workshops Vijay Veerabadran, Reza Pourreza, Amirhossein Habibian, Taco Cohen
2020	J	`jnl`	Adversarial Distortion for Learned Video Compression. CoRR Vijay Veerabadran, Reza Pourreza, Amirhossein Habibian, Taco Cohen
2020	J	`jnl`	Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs. CoRR Pim de Haan, Maurice Weiler, Taco Cohen, Max Welling
2020	A*	`conf`	Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks. ICML Adeel Pervez, Taco Cohen, Efstratios Gavves
2020	J	`jnl`	Natural Graph Networks. CoRR Pim de Haan, Taco Cohen, Max Welling
2020	C	`conf`	Parallelized Rate-Distortion Optimized Quantization Using Deep Learning. MMSP Dana Kianfar, Auke J. Wiggers, Amir Said, Reza Pourreza, Taco Cohen
2020	J	`jnl`	Parallelized Rate-Distortion Optimized Quantization Using Deep Learning. CoRR Dana Kianfar, Auke J. Wiggers, Amir Said, Reza Pourreza, Taco Cohen
2020	J	`jnl`	Teacher-Student Curriculum Learning. IEEE Trans. Neural Networks Learn. Syst. Tambet Matiisen, Avital Oliver, Taco Cohen, John Schulman
2019	A*	`conf`	Gauge Equivariant Convolutional Networks and the Icosahedral CNN. ICML Taco Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling
2019	A*	`conf`	Video Compression With Rate-Distortion Autoencoders. ICCV Amirhossein Habibian, Ties van Rozendaal, Jakub M. Tomczak, Taco Cohen
2018	A*	`conf`	3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. NeurIPS Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen
2018	J	`jnl`	3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. CoRR Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma, Taco Cohen
2018	J	`jnl`	A General Theory of Equivariant CNNs on Homogeneous Spaces. CoRR Taco Cohen, Mario Geiger, Maurice Weiler
2018	—	`conf`	Rotation Equivariant CNNs for Digital Pathology. MICCAI (2) Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
2018	J	`jnl`	Rotation Equivariant CNNs for Digital Pathology. CoRR Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
2017	J	`jnl`	Convolutional Networks for Spherical Signals. CoRR Taco Cohen, Mario Geiger, Jonas Köhler, Max Welling
2017	J	`jnl`	Teacher-Student Curriculum Learning. CoRR Tambet Matiisen, Avital Oliver, Taco Cohen, John Schulman
2016	A*	`conf`	Group Equivariant Convolutional Networks. ICML Taco Cohen, Max Welling
2015	A*	`conf`	Harmonic Exponential Families on Manifolds. ICML Taco Cohen, Max Welling
2014	A*	`conf`	Learning the Irreducible Representations of Commutative Lie Groups. ICML Taco Cohen, Max Welling
2014	J	`jnl`	Learning the Irreducible Representations of Commutative Lie Groups. CoRR Taco Cohen, Max Welling