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ORCIDAlexander Nikulin
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2020 – today
- 2024
[c7]Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov:
In-Context Reinforcement Learning for Variable Action Spaces. ICML 2024- [c6]Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov:
Emergence of In-Context Reinforcement Learning from Noise Distillation. ICML 2024 - [i13]Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad H. Danesh, Cyril Roumégous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João G. M. Araújo, Guorui Quan, Daniel Tan, Timo Klein, Rujikorn Charakorn, Mark Towers, Yann Berthelot, Kinal Mehta, Dipam Chakraborty, Arjun KG, Valentin Charraut, Chang Ye, Zichen Liu, Lucas N. Alegre, Alexander Nikulin, Xiao Hu, Tianlin Liu, Jongwook Choi, Brent Yi:
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning. CoRR abs/2402.03046 (2024) - [i12]Alexander Nikulin, Ilya Zisman, Alexey Zemtsov, Viacheslav Sinii, Vladislav Kurenkov, Sergey Kolesnikov:
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning. CoRR abs/2406.08973 (2024) - [i11]Ilya Zisman, Alexander Nikulin, Andrei Polubarov, Nikita Lyubaykin, Vladislav Kurenkov:
N-Gram Induction Heads for In-Context RL: Improving Stability and Reducing Data Needs. CoRR abs/2411.01958 (2024) - 2023
- [c5]Alexander Nikulin
, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov:
Anti-Exploration by Random Network Distillation. ICML 2023: 26228-26244 - [c4]Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Katakomba: Tools and Benchmarks for Data-Driven NetHack. NeurIPS 2023 - [c3]Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov:
Revisiting the Minimalist Approach to Offline Reinforcement Learning. NeurIPS 2023 - [c2]Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov:
CORL: Research-oriented Deep Offline Reinforcement Learning Library. NeurIPS 2023 - [i10]Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov:
Anti-Exploration by Random Network Distillation. CoRR abs/2301.13616 (2023) - [i9]Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov:
Revisiting the Minimalist Approach to Offline Reinforcement Learning. CoRR abs/2305.09836 (2023) - [i8]Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Katakomba: Tools and Benchmarks for Data-Driven NetHack. CoRR abs/2306.08772 (2023) - [i7]Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov:
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. CoRR abs/2312.12044 (2023) - [i6]Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov:
Emergence of In-Context Reinforcement Learning from Noise Distillation. CoRR abs/2312.12275 (2023) - [i5]Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov:
In-Context Reinforcement Learning for Variable Action Spaces. CoRR abs/2312.13327 (2023) - 2022
- [i4]Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman:
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. CoRR abs/2202.10583 (2022) - [i3]Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov:
CORL: Research-oriented Deep Offline Reinforcement Learning Library. CoRR abs/2210.07105 (2022) - [i2]Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Dmitry Akimov, Sergey Kolesnikov:
Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size. CoRR abs/2211.11092 (2022) - [i1]Dmitriy Akimov, Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov:
Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows. CoRR abs/2211.11096 (2022) - 2021
- [c1]Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman:
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) 2021: 13-28
Coauthor Index
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