Alexander Nikulin

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 17

Top Topics

Temporal Difference

Reinforcement Learning

Direct Policy Search

Top Venues

NeurIPS (Competition and Demos)

Publications

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 (2024)
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 (2024)
Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
Katakomba: Tools and Benchmarks for Data-Driven NetHack. CoRR (2023)
Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov
Revisiting the Minimalist Approach to Offline Reinforcement Learning. CoRR (2023)
Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov
Revisiting the Minimalist Approach to Offline Reinforcement Learning. NeurIPS (2023)
Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov
Anti-Exploration by Random Network Distillation. ICML (2023)
Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. CoRR (2023)
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov
In-Context Reinforcement Learning for Variable Action Spaces. CoRR (2023)
Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov
Anti-Exploration by Random Network Distillation. CoRR (2023)
Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov
Emergence of In-Context Reinforcement Learning from Noise Distillation. CoRR (2023)
Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov
CORL: Research-oriented Deep Offline Reinforcement Learning Library. NeurIPS (2023)
Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
Katakomba: Tools and Benchmarks for Data-Driven NetHack. NeurIPS (2023)
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 (2022)
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 (2022)
Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov
CORL: Research-oriented Deep Offline Reinforcement Learning Library. CoRR (2022)
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 (2022)
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)