Pierre-Alexandre Kamienny

According to our database, Pierre-Alexandre Kamienny authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulos, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim

CoRR, 2024

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

PhD thesis, 2023

Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search.

Pierre-Alexandre Kamienny, Guillaume Lample, Sylvain Lamprier, Marco Virgolin

Proceedings of the International Conference on Machine Learning, 2023

Controllable Neural Symbolic Regression.

Tommaso Bendinelli, Luca Biggio, Pierre-Alexandre Kamienny

Proceedings of the International Conference on Machine Learning, 2023

2022

Deep Symbolic Regression for Recurrent Sequences.

Stéphane d'Ascoli, Pierre-Alexandre Kamienny, Guillaume Lample, François Charton

CoRR, 2022

End-to-end Symbolic Regression with Transformers.

Pierre-Alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, François Charton

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep symbolic regression for recurrence prediction.

Stéphane d'Ascoli, Pierre-Alexandre Kamienny, Guillaume Lample, François Charton

Proceedings of the International Conference on Machine Learning, 2022

Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching.

Pierre-Alexandre Kamienny, Jean Tarbouriech, Sylvain Lamprier, Alessandro Lazaric, Ludovic Denoyer

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching.

Pierre-Alexandre Kamienny, Jean Tarbouriech, Alessandro Lazaric, Ludovic Denoyer

CoRR, 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

FACMAC: Factored Multi-Agent Centralised Policy Gradients.

Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Privileged Information Dropout in Reinforcement Learning.

Pierre-Alexandre Kamienny, Kai Arulkumaran, Feryal M. P. Behbahani, Wendelin Boehmer, 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

Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control.

Christian Schröder de Witt, Bei Peng, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Böhmer, Shimon Whiteson

CoRR, 2020