| Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ... nature 518 (7540), 529-533, 2015 | 29423 | 2015 |
| Overcoming catastrophic forgetting in neural networks J Kirkpatrick, R Pascanu, N Rabinowitz, J Veness, G Desjardins, AA Rusu, ... Proceedings of the national academy of sciences 114 (13), 3521-3526, 2017 | 6577 | 2017 |
| The arcade learning environment: An evaluation platform for general agents MG Bellemare, Y Naddaf, J Veness, M Bowling Journal of Artificial Intelligence Research, 2013 | 3429 | 2013 |
| Monte-Carlo planning in large POMDPs D Silver, J Veness Advances in neural information processing systems 23, 2010 | 1409 | 2010 |
| Revisiting the arcade learning environment: Evaluation protocols and open problems for general agents MC Machado, MG Bellemare, E Talvitie, J Veness, M Hausknecht, ... Journal of Artificial Intelligence Research 61, 523-562, 2018 | 590 | 2018 |
| A Monte-Carlo AIXI Approximation J Veness, KS Ng, M Hutter, W Uther, D Silver Journal of Artificial Intelligence Research 40 (1), 95-142, 2011 | 219 | 2011 |
| Investigating contingency awareness using Atari 2600 games M Bellemare, J Veness, M Bowling Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 864-871, 2012 | 108 | 2012 |
| Bootstrapping from Game Tree Search J Veness, D Silver, A Blair, W Uther Advances in neural information processing systems, 1937-1945, 2009 | 87 | 2009 |
| & Petersen, S.(2015). Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare Nature 518 (7540), 529, 0 | 87 | |
| Meta-learning of sequential strategies PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ... arXiv preprint arXiv:1905.03030, 2019 | 82 | 2019 |
| An approximation of the universal intelligence measure S Legg, J Veness Ray Solomonoff Memorial Conference 2011, 2011 | 79 | 2011 |
| & Hassabis, D.(2015) V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare Human-level control through deep reinforcement learning. nature 518 (7540 …, 0 | 79 | |
| 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 | 74 | 2022 |
| Context tree switching J Veness, KS Ng, M Hutter, M Bowling 2012 data compression conference, 327-336, 2012 | 54 | 2012 |
| Skip context tree switching M Bellemare, J Veness, E Talvitie International conference on machine learning, 1458-1466, 2014 | 51 | 2014 |
| 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 | 42 | 2021 |
| Language modeling is compression G Delétang, A Ruoss, PA Duquenne, E Catt, T Genewein, C Mattern, ... arXiv preprint arXiv:2309.10668, 2023 | 41 | 2023 |
| Bayesian Learning of Recursively Factored Environments M Bellemare, J Veness, M Bowling ICML 2013, 2013 | 40 | 2013 |
| 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 | 35 | 2023 |
| Gated linear networks J Veness, T Lattimore, D Budden, A Bhoopchand, C Mattern, ... Proceedings of the AAAI conference on artificial intelligence 35 (11), 10015 …, 2021 | 35 | 2021 |
Marc G. BellemareGoogle BrainEmail verificata su google.com
