| Neural Networks and the Chomsky Hierarchy G Delétang, A Ruoss, J Grau-Moya, T Genewein, LK Wenliang, E Catt, ... International Conference on Learning Representations 11, 2022 | 139 | 2022 |
| Language Modeling is Compression G Delétang, A Ruoss, PA Duquenne, E Catt, T Genewein, C Mattern, ... International Conference on Learning Representations 12, 2023 | 138 | 2023 |
| Randomized Positional Encodings Boost Length Generalization of Transformers A Ruoss, G Delétang, T Genewein, J Grau-Moya, R Csordás, M Bennani, ... 61st Annual Meeting of the Association for Computational Linguistics, 2023 | 83 | 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 | 66 | 2021 |
| Meta-trained agents implement Bayes-Optimal agents V Mikulik, G Delétang, T McGrath, T Genewein, M Martic, S Legg, ... Advances in Neural Information Processing Systems 33, 2020 | 47 | 2020 |
| Evaluating frontier models for dangerous capabilities M Phuong, M Aitchison, E Catt, S Cogan, A Kaskasoli, V Krakovna, ... arXiv preprint arXiv:2403.13793, 2024 | 45 | 2024 |
| 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 | 33 | 2024 |
| Algorithms for causal reasoning in probability trees T Genewein, T McGrath, G Delétang, V Mikulik, M Martic, S Legg, ... arXiv preprint arXiv:2010.12237, 2020 | 23 | 2020 |
| Model-free risk-sensitive reinforcement learning G Delétang, J Grau-Moya, M Kunesch, T Genewein, R Brekelmans, ... arXiv preprint arXiv:2111.02907, 2021 | 13 | 2021 |
| Your policy regularizer is secretly an adversary R Brekelmans, T Genewein, J Grau-Moya, G Delétang, M Kunesch, ... arXiv preprint arXiv:2203.12592, 2022 | 11 | 2022 |
| Causal Analysis of Agent Behavior for AI Safety G Déletang, J Grau-Moya, M Martic, T Genewein, T McGrath, V Mikulik, ... arXiv preprint arXiv:2103.03938, 2021 | 11 | 2021 |
| Learning Universal Predictors J Grau-Moya, T Genewein, M Hutter, L Orseau, G Delétang, E Catt, ... arXiv preprint arXiv:2401.14953, 2024 | 10 | 2024 |
| Memory-Based Meta-Learning on Non-Stationary Distributions T Genewein, G Delétang, A Ruoss, LK Wenliang, E Catt, V Dutordoir, ... International Conference on Machine Learning 40, 2023 | 9 | 2023 |
| Distributional Bellman Operators over Mean Embeddings LK Wenliang, G Déletang, M Aitchison, M Hutter, A Ruoss, A Gretton, ... arXiv preprint arXiv:2312.07358, 2023 | 4 | 2023 |
| Self-Predictive Universal AI E Catt, J Grau-Moya, M Hutter, M Aitchison, T Genewein, G Deletang, ... Advances in Neural Information Processing Systems 37, 2023 | 4 | 2023 |
| Beyond Bayes-optimality: meta-learning what you know you don't know J Grau-Moya, G Delétang, M Kunesch, T Genewein, E Catt, K Li, A Ruoss, ... arXiv preprint arXiv:2209.15618, 2022 | 3 | 2022 |
| Amortized planning with large-scale transformers: A case study on chess A Ruoss, G Deletang, S Medapati, J Grau-Moya, LK Wenliang, E Catt, ... The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 2 | 2024 |
| Policy Gradient without Boostrapping via Truncated Value Learning M Aitchison, P Sweetser, G Deletang, M Hutter | | |
| Generative Reinforcement Learning with Transformers G Deletang, A Ruoss, LK Wenliang, E Catt, T Genewein, J Grau-Moya, ... | | |
Tim GeneweinDeepMindBestätigte E-Mail-Adresse bei google.com