| A Constrained Multi-Objective Reinforcement Learning Framework S Huang, A Abdolmaleki, G Vezzani, P Brakel, DJ Mankowitz, M Neunert, ... 5th Annual Conference on Robot Learning, 2021 | 21 | 2021 |
| A Distributional View on Multi-Objective Policy Optimization A Abdolmaleki, SH Huang, L Hasenclever, M Neunert, HF Song, ... arXiv preprint arXiv:2005.07513, 2020 | 77 | 2020 |
| A Distributional View on Multi-Objective Policy Optimization Download PDF A Abdolmaleki, SH Huang, L Hasenclever, M Neunert, HF Song, ... | | |
| A Generalist Agent S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ... arXiv preprint arXiv:2205.06175, 2022 | 763 | 2022 |
| A Generalist Dynamics Model for Control I Schubert, J Zhang, J Bruce, S Bechtle, E Parisotto, M Riedmiller, ... arXiv preprint arXiv:2305.10912, 2023 | 16 | 2023 |
| A Generalized Training Approach for Multiagent Learning P Muller, S Omidshafiei, M Rowland, K Tuyls, J Perolat, S Liu, D Hennes, ... arXiv preprint arXiv:1909.12823, 2019 | 106 | 2019 |
| A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning K Khetarpal, ZD Guo, BA Pires, Y Tang, C Lyle, M Rowland, N Heess, ... arXiv preprint arXiv:2406.02035, 2024 | | 2024 |
| Action and Perception as Divergence Minimization D Hafner, PA Ortega, J Ba, T Parr, K Friston, N Heess arXiv preprint arXiv:2009.01791, 2020 | 58 | 2020 |
| Actor-Critic Reinforcement Learning with Energy-Based Policies. N Heess, D Silver, YW Teh EWRL, 43-58, 2012 | 109 | 2012 |
| Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions L Buesing, N Heess, T Weber arXiv preprint arXiv:1910.06862, 2019 | 12 | 2019 |
| Attend, Infer, Repeat: Fast Scene Understanding with Deep Generative Models SMA Eslami, N Heess, T Weber, Y Tassa | | |
| Attend, infer, repeat: Fast scene understanding with generative models SMA Eslami, N Heess, T Weber, Y Tassa, D Szepesvari, GE Hinton Advances in Neural Information Processing Systems, 3225-3233, 2016 | 586 | 2016 |
| Attend, Infer, Repeat: Fast Scene Understanding with Generative Models arXiv: 1603.08575 v1 SMA Eslami, N Heess, T Weber, Y Tassa, K Kavukcuoglu | | 2016 |
| Barkour: Benchmarking Animal-level Agility with Quadruped Robots K Caluwaerts, A Iscen, JC Kew, W Yu, T Zhang, D Freeman, KH Lee, ... arXiv preprint arXiv:2305.14654, 2023 | 24 | 2023 |
| Bayes-adaptive simulation-based search with value function approximation A Guez, N Heess, D Silver, P Dayan Advances in Neural Information Processing Systems, 451-459, 2014 | 33 | 2014 |
| Behavior Priors for Efficient Reinforcement Learning D Tirumala, A Galashov, H Noh, L Hasenclever, R Pascanu, J Schwarz, ... arXiv preprint arXiv:2010.14274, 2020 | 33 | 2020 |
| Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban P Karkus, M Mirza, A Guez, A Jaegle, T Lillicrap, L Buesing, N Heess, ... arXiv preprint arXiv:2010.01298, 2020 | 7 | 2020 |
| Catch & Carry: reusable neural controllers for vision-guided whole-body tasks J Merel, S Tunyasuvunakool, A Ahuja, Y Tassa, L Hasenclever, V Pham, ... ACM Transactions on Graphics (TOG) 39 (4), 39: 1-39: 12, 2020 | 116 | 2020 |
| Coherent Soft Imitation Learning J Watson, SH Huang, N Heess arXiv preprint arXiv:2305.16498, 2023 | 3 | 2023 |
| Collect & Infer--a fresh look at data-efficient Reinforcement Learning M Riedmiller, JT Springenberg, R Hafner, N Heess arXiv preprint arXiv:2108.10273, 2021 | 21 | 2021 |
