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Léonard Hussenot
Léonard Hussenot
Google DeepMind
在 google.com 的电子邮件经过验证 - 首页
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引用次数
引用次数
年份
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
9912023
What matters for on-policy deep actor-critic methods? a largescale study
M Andrychowicz, A Raichuk, P Stanczyk, M Orsini, S Girgin, R Marinier, ...
International Conference on Learning Representations (ICLR), 2021, 2021
402*2021
Gemma: Open models based on gemini research and technology
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
arXiv preprint arXiv:2403.08295, 2024
2582024
Acme: A research framework for distributed reinforcement learning
MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ...
arXiv preprint arXiv:2006.00979, 2022
2412022
Primal wasserstein imitation learning
R Dadashi, L Hussenot, M Geist, O Pietquin
International Conference on Learning Representations (ICLR), 2021, 2020
1302020
What Matters for Adversarial Imitation Learning?
M Orsini*, A Raichuk*, L Hussenot*, D Vincent, R Dadashi, S Girgin, ...
NeurIPS 35th Conference on Neural Information Processing Systems, 2021
672021
Offline Reinforcement Learning as Anti-Exploration
S Rezaeifar, R Dadashi, N Vieillard, L Hussenot, O Bachem, O Pietquin, ...
AAAI 2022, 2021
502021
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
P Roit, J Ferret, L Shani, R Aharoni, G Cideron, R Dadashi, M Geist, ...
ACL 2023 Proceedings, forthcoming. Association for Computational Linguistics, 2023
422023
Offline Reinforcement Learning with Pseudometric Learning
R Dadashi, S Rezaeifar, N Vieillard, L Hussenot, O Pietquin, M Geist
International Conference on Machine Learning (ICML), 2021, 2021
382021
CopyCAT: Taking control of neural policies with constant attacks
L Hussenot, M Geist, O Pietquin
International Conference on Autonomous Agents and Multiagent Systems (AAMAS …, 2019
302019
Continuous Control with Action Quantization from Demonstrations
R Dadashi*, L Hussenot*, D Vincent, S Girgin, A Raichuk, M Geist, ...
International Conference on Machine Learning (ICML), 2022, 2021
282021
Warm: On the benefits of weight averaged reward models
A Ramé, N Vieillard, L Hussenot, R Dadashi, G Cideron, O Bachem, ...
arXiv preprint arXiv:2401.12187, 2024
252024
Targeted attacks on deep reinforcement learning agents through adversarial observations
L Hussenot, M Geist, O Pietquin
ICML Workshop, 2020
222020
Hyperparameter Selection for Imitation Learning
L Hussenot, M Andrychowicz, D Vincent, R Dadashi, A Raichuk, ...
International Conference on Machine Learning (ICML), 2021, 2021
172021
Rlds: an ecosystem to generate, share and use datasets in reinforcement learning
S Ramos, S Girgin, L Hussenot, D Vincent, H Yakubovich, D Toyama, ...
arXiv preprint arXiv:2111.02767, 2021
122021
Show me the Way: Intrinsic Motivation from Demonstrations
L Hussenot, R Dadashi, M Geist, O Pietquin
International Conference on Autonomous Agents and Multiagent Systems (AAMAS …, 2020
102020
Musicrl: Aligning music generation to human preferences
G Cideron, S Girgin, M Verzetti, D Vincent, M Kastelic, Z Borsos, ...
arXiv preprint arXiv:2402.04229, 2024
62024
Learning Energy Networks with Generalized Fenchel-Young Losses
M Blondel, F Llinares-López, R Dadashi, L Hussenot, M Geist
NeurIPS 36th Conference on Neural Information Processing Systems, 2022
62022
Get back here: Robust imitation by return-to-distribution planning
G Cideron, B Tabanpour, S Curi, S Girgin, L Hussenot, G Dulac-Arnold, ...
arXiv preprint arXiv:2305.01400, 2023
42023
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
A Botev, S De, SL Smith, A Fernando, GC Muraru, R Haroun, L Berrada, ...
arXiv preprint arXiv:2404.07839, 2024
22024
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