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ORCIDAdrien Ali Taïga
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2020 – today
- 2024
[c7]Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal:
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. ICML 2024- [i8]Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal:
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. CoRR abs/2403.03950 (2024) - 2023
- [c6]Adrien Ali Taïga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare:
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning. ICLR 2023 - 2021
- [i7]Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare:
On Bonus-Based Exploration Methods in the Arcade Learning Environment. CoRR abs/2109.11052 (2021) - 2020
- [c5]Adrien Ali Taïga, William Fedus, Marlos C. Machado
, Aaron C. Courville, Marc G. Bellemare:
On Bonus Based Exploration Methods In The Arcade Learning Environment. ICLR 2020 - [i6]Ahmed Touati, Adrien Ali Taïga, Marc G. Bellemare:
Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces. CoRR abs/2003.04069 (2020)
2010 – 2019
- 2019
- [c4]Robert Dadashi, Marc G. Bellemare, Adrien Ali Taïga, Nicolas Le Roux, Dale Schuurmans:
The Value Function Polytope in Reinforcement Learning. ICML 2019: 1486-1495 - [c3]Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle:
A Geometric Perspective on Optimal Representations for Reinforcement Learning. NeurIPS 2019: 4360-4371 - [i5]Robert Dadashi, Adrien Ali Taïga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare:
The Value Function Polytope in Reinforcement Learning. CoRR abs/1901.11524 (2019) - [i4]Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle:
A Geometric Perspective on Optimal Representations for Reinforcement Learning. CoRR abs/1901.11530 (2019) - [i3]Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare:
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment. CoRR abs/1908.02388 (2019) - 2018
- [c2]Florian Golemo, Adrien Ali Taïga, Aaron C. Courville, Pierre-Yves Oudeyer:
Sim-to-Real Transfer with Neural-Augmented Robot Simulation. CoRL 2018: 817-828 - [i2]Adrien Ali Taïga, Aaron C. Courville, Marc G. Bellemare:
Approximate Exploration through State Abstraction. CoRR abs/1808.09819 (2018) - 2017
- [c1]Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taïga, Francesco Visin, David Vázquez, Aaron C. Courville:
PixelVAE: A Latent Variable Model for Natural Images. ICLR (Poster) 2017 - 2016
- [i1]Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed, Adrien Ali Taïga, Francesco Visin, David Vázquez, Aaron C. Courville:
PixelVAE: A Latent Variable Model for Natural Images. CoRR abs/1611.05013 (2016)
Coauthor Index
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