Pierre-Alexandre Kamienny
Pierre-Alexandre Kamienny
Meta AI (FAIR)
Verified email at - Homepage
Cited by
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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
Deep symbolic regression for recurrence prediction
S d’Ascoli, PA Kamienny, G Lample, F Charton
International Conference on Machine Learning (ICML), 2022
End-to-end symbolic regression with transformers
PA Kamienny, S d'Ascoli, G Lample, F Charton
Neural Information Processing Systems (NeurIPS), 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
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
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
Salina: Sequential learning of agents
L Denoyer, A De la Fuente, S Duong, JB Gaya, PA Kamienny, ...
arXiv preprint arXiv:2110.07910, 2021
MTEnv-environment interface for multi-task reinforcement learning
S Sodhani, L Denoyer, PA Kamienny, O Delalleau
Github, 2021a. URL https://github. com/facebookresearch/mtenv, 2021
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
PA Kamienny, G Lample, S Lamprier, M Virgolin
arXiv preprint arXiv:2302.11223, 2023
Privileged Deep Symbolic Regression
L Biggio, B Tommaso, PA Kamienny
Neural Information Processing Systems (NeurIPS) 2022 AI for Science …, 2022
Symbolic-Model-Based Reinforcement Learning
PA Kamienny, S Lamprier
Neural Information Processing Systems (NeurIPS) 2022 AI for Science …, 2022
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