| Language Modeling Is Compression G Delétang, A Ruoss, PA Duquenne, E Catt, T Genewein, C Mattern, ... arXiv preprint arXiv:2309.10668, 2023 | 163 | 2023 |
| Neural networks and the chomsky hierarchy G Delétang, A Ruoss, J Grau-Moya, T Genewein, LK Wenliang, E Catt, ... arXiv preprint arXiv:2207.02098, 2022 | 145 | 2022 |
| Bounded rationality, abstraction and hierarchical decision-making: an information-theoretic optimality principle T Genewein, F Leibfried, J Grau-Moya, DAB Braun Frontiers in Robotics and AI 2, 27, 2015 | 130 | 2015 |
| Randomized Positional Encodings Boost Length Generalization of Transformers A Ruoss, G Delétang, T Genewein, J Grau-Moya, R Csordás, M Bennani, ... arXiv preprint arXiv:2305.16843, 2023 | 88 | 2023 |
| Shaking the foundations: delusions in sequence models for interaction and control PA Ortega, M Kunesch, G Delétang, T Genewein, J Grau-Moya, J Veness, ... arXiv preprint arXiv:2110.10819, 2021 | 65 | 2021 |
| Soft Q-Learning with Mutual-Information Regularization J Grau-Moya, F Leibfried, P Vrancx International Conference on Learning Representations (ICLR), 2019 | 64 | 2019 |
| Balancing Two-Player Stochastic Games with Soft Q-Learning J Grau-Moya, F Leibfried, H Bou-Ammar Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 59 | 2018 |
| Signaling equilibria in sensorimotor interactions. F Leibfried, J Grau-Moya, DA Braun Cognition 141, 73-86, 2015 | 48 | 2015 |
| A unified bellman optimality principle combining reward maximization and empowerment F Leibfried, S Pascual-Diaz, J Grau-Moya Advances in Neural Information Processing Systems, 7869-7880, 2019 | 43 | 2019 |
| Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes J Grau-Moya, F Leibfried, T Genewein, DA Braun Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 39 | 2016 |
| Grandmaster-level chess without search A Ruoss, G Delétang, S Medapati, J Grau-Moya, LK Wenliang, E Catt, ... arXiv e-prints, arXiv: 2402.04494, 2024 | 36 | 2024 |
| An information-theoretic optimality principle for deep reinforcement learning F Leibfried, J Grau-Moya, H Bou-Ammar NeurIPS Workshop on Deep Reinforcement Learning, 2017 | 32 | 2017 |
| Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning F Leibfried, J Grau-Moya Conference on Robot Learning (CoRL), 2019 | 26 | 2019 |
| The effect of model uncertainty on cooperation in sensorimotor interactions J Grau-Moya, E Hez, G Pezzulo, DA Braun Journal of The Royal Society Interface 10 (87), 20130554, 2013 | 24 | 2013 |
| Risk-Sensitivity in Bayesian Sensorimotor Integration J Grau-Moya, PA Ortega, DA Braun PLOS Computational Biology 8 (9), e1002698, 2012 | 21 | 2012 |
| Disentangled Skill Embeddings for Reinforcement Learning JC Petangoda, S Pascual-Diaz, V Adam, P Vrancx, J Grau-Moya NeurIPS Workshop on Learning Transferable Skills, 2019 | 20 | 2019 |
| Non-equilibrium relations for bounded rational decision-making in changing environments J Grau-Moya, M Krüger, DA Braun Entropy 20 (1), 1, 2017 | 15 | 2017 |
| Learning Universal Predictors J Grau-Moya, T Genewein, M Hutter, L Orseau, G Delétang, E Catt, ... Proceedings of the 41st International Conference on Machine Learning, PMLR …, 2024 | 14 | 2024 |
| Your Policy Regularizer is Secretly an Adversary R Brekelmans, T Genewein, J Grau-Moya, G Delétang, M Kunesch, ... arXiv preprint arXiv:2203.12592, 2022 | 14 | 2022 |
| Model-Free Risk-Sensitive Reinforcement Learning G Delétang, J Grau-Moya, M Kunesch, T Genewein, R Brekelmans, ... arXiv preprint arXiv:2111.02907, 2021 | 14 | 2021 |
Tim GeneweinDeepMindVerified email at google.com
