FACMAC: Factored multi-agent centralised policy gradients B Peng, T Rashid, C Schroeder de Witt, PA Kamienny, P Torr, W Böhmer, ... Neural Information Processing Systems (NeurIPS), 2021 | 235* | 2021 |
End-to-end symbolic regression with transformers PA Kamienny, S d'Ascoli, G Lample, F Charton Neural Information Processing Systems (NeurIPS), 2022 | 101 | 2022 |
Deep symbolic regression for recurrence prediction S d’Ascoli, PA Kamienny, G Lample, F Charton International Conference on Machine Learning (ICML), 2022 | 59* | 2022 |
Meta-Reinforcement Learning With Informed Policy Regularization PA Kamienny, M Pirotta, A Lazaric, T Lavril, N Usunier, L Denoyer ICML 2020 Workshop on Inductive Biases, Invariances and Generalization in RL …, 2020 | 21* | 2020 |
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching PA Kamienny, J Tarbouriech, S Lamprier, A Lazaric, L Denoyer International Conference on Learning Representations (ICLR), 2022 | 16 | 2022 |
Privileged information dropout in reinforcement learning PA Kamienny, K Arulkumaran, F Behbahani, W Boehmer, S Whiteson ICLR 2020 Workshop on Beyond tabula rasa in RL (BeTR-RL), 2020 | 13 | 2020 |
Salina: Sequential learning of agents L Denoyer, A De la Fuente, S Duong, JB Gaya, PA Kamienny, ... arXiv preprint arXiv:2110.07910, 2021 | 12 | 2021 |
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search PA Kamienny, G Lample, S Lamprier, M Virgolin International Conference on Machine Learning (ICML), 2023 | 10 | 2023 |
Interpretable symbolic regression for data science: Analysis of the 2022 competition FO de França, M Virgolin, M Kommenda, MS Majumder, M Cranmer, ... arXiv preprint arXiv:2304.01117, 2023 | 6 | 2023 |
Mtenv-environment interface for mulit-task reinforcement learning S Sodhani, L Denoyer, PA Kamienny, O Delalleau Github, 2021a. URL https://github. com/facebookresearch/mtenv, 2021 | 6 | 2021 |
Controllable Neural Symbolic Regression T Bendinelli, L Biggio, PA Kamienny International Conference on Machine Learning (ICML), 2023 | 5* | 2023 |
Symbolic-Model-Based Reinforcement Learning PA Kamienny, S Lamprier Neural Information Processing Systems (NeurIPS) 2022 AI for Science …, 2022 | 1 | 2022 |
Efficient adaptation of reinforcement learning agents: from model-free exploration to symbolic world models PA Kamienny Sorbonne Université, 2023 | | 2023 |