Alexander Nikulin

According to our database, Alexander Nikulin authored at least 13 papers between 2021 and 2024.

Collaborative distances:

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

2024

N-Gram Induction Heads for In-Context RL: Improving Stability and Reducing Data Needs.

Ilya Zisman, Alexander Nikulin, Andrei Polubarov, Nikita Lyubaykin, Vladislav Kurenkov

CoRR, 2024

XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning.

Alexander Nikulin, Ilya Zisman, Alexey Zemtsov, Viacheslav Sinii, Vladislav Kurenkov, Sergey Kolesnikov

CoRR, 2024

Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.

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

CoRR, 2024

Emergence of In-Context Reinforcement Learning from Noise Distillation.

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov

Proceedings of the Forty-first International Conference on Machine Learning, 2024

In-Context Reinforcement Learning for Variable Action Spaces.

Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX.

Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov

CoRR, 2023

CORL: Research-oriented Deep Offline Reinforcement Learning Library.

Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Revisiting the Minimalist Approach to Offline Reinforcement Learning.

Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Katakomba: Tools and Benchmarks for Data-Driven NetHack.

Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Anti-Exploration by Random Network Distillation.

Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov

Proceedings of the International Conference on Machine Learning, 2023

2022

Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows.

Dmitriy Akimov, Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov

CoRR, 2022

Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size.

Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Dmitry Akimov, Sergey Kolesnikov

CoRR, 2022

2021

MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned.

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

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021