Sergey Kolesnikov

53 papers A* 8A 3B 1Journal 31Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection. WACV Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov
2024	B	`conf`	Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy. ICIP Stanislav Dereka, Ivan Karpukhin, Maksim Zhdanov, Sergey Kolesnikov
2024	J	`jnl`	EXACT: How to train your accuracy. Pattern Recognit. Lett. Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
2024	A*	`conf`	Emergence of In-Context Reinforcement Learning from Noise Distillation. ICML Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov
2024	A*	`conf`	In-Context Reinforcement Learning for Variable Action Spaces. ICML Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov
2024	J	`jnl`	Probabilistic embeddings revisited. Vis. Comput. Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
2024	A	`conf`	Revisiting BPR: A Replicability Study of a Common Recommender System Baseline. RecSys Aleksandr Milogradskii, Oleg Lashinin, Alexander P, Marina Ananyeva, Sergey Kolesnikov
2024	J	`jnl`	Revisiting BPR: A Replicability Study of a Common Recommender System Baseline. CoRR Aleksandr Milogradskii, Oleg Lashinin, Alexander P, Marina Ananyeva, Sergey Kolesnikov
2024	J	`jnl`	XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning. CoRR Alexander Nikulin, Ilya Zisman, Alexey Zemtsov, Viacheslav Sinii, Vladislav Kurenkov, Sergey Kolesnikov
2024	A*	`conf`	XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. NeurIPS Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov
2023	A*	`conf`	Anti-Exploration by Random Network Distillation. ICML Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov
2023	J	`jnl`	Anti-Exploration by Random Network Distillation. CoRR Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Sergey Kolesnikov
2023	A*	`conf`	CORL: Research-oriented Deep Offline Reinforcement Learning Library. NeurIPS Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov
2023	J	`jnl`	Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy. CoRR Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov
2023	J	`jnl`	Emergence of In-Context Reinforcement Learning from Noise Distillation. CoRR Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin, Viacheslav Sinii, Sergey Kolesnikov
2023	—	`conf`	GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram. KaRS@RecSys Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov
2023	J	`jnl`	In-Context Reinforcement Learning for Variable Action Spaces. CoRR Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Sergey Kolesnikov
2023	A*	`conf`	Katakomba: Tools and Benchmarks for Data-Driven NetHack. NeurIPS Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
2023	J	`jnl`	Katakomba: Tools and Benchmarks for Data-Driven NetHack. CoRR Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
2023	—	`conf`	Make your next item recommendation model time sensitive. UMAP (Adjunct Publication) Elizaveta Makhneva, Anna Sverkunova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
2023	—	`conf`	Next-basket Recommendation Constrained by Total Cost. ORSUM@RecSys Denis Krasilnikov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
2023	—	`conf`	RecBaselines2023: a new dataset for choosing baselines for recommender models. BIR@ECIR Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
2023	J	`jnl`	RecBaselines2023: a new dataset for choosing baselines for recommender models. CoRR Veronika Ivanova, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
2023	A*	`conf`	Revisiting the Minimalist Approach to Offline Reinforcement Learning. NeurIPS Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov
2023	J	`jnl`	Revisiting the Minimalist Approach to Offline Reinforcement Learning. CoRR Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov
2023	A	`conf`	Time-Aware Item Weighting for the Next Basket Recommendations. RecSys Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
2023	J	`jnl`	Time-Aware Item Weighting for the Next Basket Recommendations. CoRR Aleksey Romanov, Oleg Lashinin, Marina Ananyeva, Sergey Kolesnikov
2023	—	`conf`	Time-Dependent Next-Basket Recommendations. ECIR (2) Sergey Naumov, Marina Ananyeva, Oleg Lashinin, Sergey Kolesnikov, Dmitry I. Ignatov
2023	J	`jnl`	Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation. CoRR Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov
2023	—	`conf`	Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations. CSW@WSDM Denis Krasilnikov, Oleg Lashinin, Maksim Tsygankov, Marina Ananyeva, Sergey Kolesnikov
2023	J	`jnl`	Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression. CoRR Sergey Kolesnikov
2023	J	`jnl`	XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. CoRR Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov
2022	J	`jnl`	CORL: Research-oriented Deep Offline Reinforcement Learning Library. CoRR Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov
2022	J	`jnl`	CVTT: Cross-Validation Through Time. CoRR Sergey Kolesnikov, Mikhail Andronov
2022	—	`conf`	Deep Image Retrieval is not Robust to Label Noise. CVPR Workshops Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov
2022	J	`jnl`	Deep Image Retrieval is not Robust to Label Noise. CoRR Stanislav Dereka, Ivan Karpukhin, Sergey Kolesnikov
2022	J	`jnl`	EXACT: How to Train Your Accuracy. CoRR Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
2022	J	`jnl`	Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows. CoRR Dmitriy Akimov, Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov
2022	J	`jnl`	Probabilistic Embeddings Revisited. CoRR Ivan Karpukhin, Stanislav Dereka, Sergey Kolesnikov
2022	J	`jnl`	Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size. CoRR Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Dmitry Akimov, Sergey Kolesnikov
2022	A*	`conf`	Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. ICML Vladislav Kurenkov, Sergey Kolesnikov
2022	—	`conf`	Towards Interaction-based User Embeddings in Sequential Recommender Models. ORSUM@RecSys Marina Ananyeva, Oleg Lashinin, Veronika Ivanova, Sergey Kolesnikov, Dmitry I. Ignatov
2021	J	`jnl`	LRWR: Large-Scale Benchmark for Lip Reading in Russian language. CoRR Evgeniy Egorov, Vasily Kostyumov, Mikhail Konyk, Sergey Kolesnikov
2021	J	`jnl`	Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. CoRR Vladislav Kurenkov, Sergey Kolesnikov
2021	J	`jnl`	TTRS: Tinkoff Transactions Recommender System benchmark. CoRR Sergey Kolesnikov, Oleg Lashinin, Michail Pechatov, Alexander Kosov
2020	J	`jnl`	Sample Efficient Ensemble Learning with Catalyst.RL. CoRR Sergey Kolesnikov, Valentin Khrulkov
2019	J	`jnl`	Artificial Intelligence for Prosthetics - challenge solutions. CoRR Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp
2019	J	`jnl`	Catalyst.RL: A Distributed Framework for Reproducible RL Research. CoRR Sergey Kolesnikov, Oleksii Hrinchuk
2018	J	`jnl`	Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. CoRR Lukasz Kidzinski, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Milos, Blazej Osinski, Andrew Melnik, Malte Schilling, Helge J. Ritter, Sean F. Carroll, Jennifer L. Hicks, Sergey Levine, Marcel Salathé, Scott L. Delp
2018	J	`jnl`	Researchers' risk-smoothing publication strategies: Is productivity the enemy of impact? Scientometrics Sergey Kolesnikov, Eriko Fukumoto, Barry Bozeman
2018	—	`conf`	Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. AAAI Spring Symposia Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
2017	J	`jnl`	Run, skeleton, run: skeletal model in a physics-based simulation. CoRR Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
2016	—	`conf`	Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules. ICUMT Yuri Parshin, Sergey Kolesnikov