Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control. - Christian Schröder de Witt; Bei Peng 001; Pierre-Alexandre Kamienny; Philip H. S. Torr; Wendelin Böhmer; Shimon Whiteson (CoRR, 2020)

Learning Adaptive Exploration Strategies in Dynamic Environments Through Informed Policy Regularization. - Pierre-Alexandre Kamienny; Matteo Pirotta; Alessandro Lazaric; Thibault Lavril; Nicolas Usunier; Ludovic Denoyer (CoRR, 2020)

Privileged Information Dropout in Reinforcement Learning. - Pierre-Alexandre Kamienny; Kai Arulkumaran; Feryal M. P. Behbahani; Wendelin Boehmer; Shimon Whiteson (CoRR, 2020)

FACMAC: Factored Multi-Agent Centralised Policy Gradients. - Bei Peng 001; Tabish Rashid; Christian Schröder de Witt; Pierre-Alexandre Kamienny; Philip H. S. Torr; Wendelin Boehmer; Shimon Whiteson (NeurIPS, 2021)

SaLinA: Sequential Learning of Agents. - Ludovic Denoyer; Alfredo De la Fuente; Song Duong; Jean-Baptiste Gaya; Pierre-Alexandre Kamienny; Daniel H. Thompson (CoRR, 2021)

Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching. - Pierre-Alexandre Kamienny; Jean Tarbouriech; Sylvain Lamprier; Alessandro Lazaric; Ludovic Denoyer (ICLR, 2022)

Deep symbolic regression for recurrence prediction. - Stéphane d'Ascoli; Pierre-Alexandre Kamienny; Guillaume Lample; François Charton (ICML, 2022)

End-to-end Symbolic Regression with Transformers. - Pierre-Alexandre Kamienny; Stéphane d'Ascoli; Guillaume Lample; François Charton (NeurIPS, 2022)

Deep Symbolic Regression for Recurrent Sequences. - Stéphane d'Ascoli; Pierre-Alexandre Kamienny; Guillaume Lample; François Charton (CoRR, 2022)

Controllable Neural Symbolic Regression. - Tommaso Bendinelli; Luca Biggio; Pierre-Alexandre Kamienny (ICML, 2023)

Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search. - Pierre-Alexandre Kamienny; Guillaume Lample; Sylvain Lamprier; Marco Virgolin (ICML, 2023)

Efficient adaptation of reinforcement learning agents : from model-free exploration to symbolic world models. (Adaptation efficace des agents appris par renforcement : de l'exploration model-free aux modèles symboliques). - Pierre-Alexandre Kamienny (2023)

Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. - Irina Jurenka; Markus Kunesch; Kevin R. McKee; Daniel Gillick; Shaojian Zhu; Sara Wiltberger; Shubham Milind Phal; Katherine L. Hermann; Daniel Kasenberg; Avishkar Bhoopchand; Ankit Anand; Miruna Pîslar; et al. (CoRR, 2024)

Evaluating Gemini in an arena for learning. - Abhinit Modi; Aditya Srikanth Veerubhotla; Aliya Rysbek; Andrea Huber; Ankit Anand; Avishkar Bhoopchand; Brett Wiltshire; Daniel Gillick; Daniel Kasenberg; Eleni Sgouritsa; Gal Elidan; Hengrui Liu; et al. (CoRR, 2025)