Adaptive filtration of random signals in active antenna array with nonlinear transmit/receive modules. - Yuri Parshin; Sergey Kolesnikov (ICUMT, 2016)

Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. - Mikhail Pavlov; Sergey Kolesnikov; Sergey M. Plis (AAAI Spring Symposia, 2018)

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. - Lukasz Kidzinski; Sharada Prasanna Mohanty; Carmichael F. Ong; Zhewei Huang; Shuchang Zhou 001; Anton Pechenko; Adam Stelmaszczyk; Piotr Jarosik; Mikhail Pavlov; Sergey Kolesnikov; Sergey M. Plis; Zhibo Chen 001; et al. (CoRR, 2018)

Researchers' risk-smoothing publication strategies: Is productivity the enemy of impact? - Sergey Kolesnikov; Eriko Fukumoto; Barry Bozeman (Scientometrics, 2018)

Artificial Intelligence for Prosthetics - challenge solutions. - Lukasz Kidzinski; Carmichael F. Ong; Sharada Prasanna Mohanty; Jennifer L. Hicks; Sean F. Carroll; Bo Zhou; Hong-cheng Zeng; Fan Wang 021; Rongzhong Lian; Hao Tian 005; Wojciech Jaskowski; Garrett Andersen; et al. (CoRR, 2019)

Catalyst.RL: A Distributed Framework for Reproducible RL Research. - Sergey Kolesnikov; Oleksii Hrinchuk (CoRR, 2019)

Sample Efficient Ensemble Learning with Catalyst.RL. - Sergey Kolesnikov; Valentin Khrulkov (CoRR, 2020)

LRWR: Large-Scale Benchmark for Lip Reading in Russian language. - Evgeniy Egorov; Vasily Kostyumov; Mikhail Konyk; Sergey Kolesnikov (CoRR, 2021)

TTRS: Tinkoff Transactions Recommender System benchmark. - Sergey Kolesnikov; Oleg Lashinin; Michail Pechatov; Alexander Kosov (CoRR, 2021)

Deep Image Retrieval is not Robust to Label Noise. - Stanislav Dereka; Ivan Karpukhin; Sergey Kolesnikov (CVPR Workshops, 2022)

Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters. - Vladislav Kurenkov; Sergey Kolesnikov (ICML, 2022)

Towards Interaction-based User Embeddings in Sequential Recommender Models. - Marina Ananyeva; Oleg Lashinin; Veronika Ivanova; Sergey Kolesnikov; Dmitry I. Ignatov (ORSUM@RecSys, 2022)

CVTT: Cross-Validation Through Time. - Sergey Kolesnikov; Mikhail Andronov (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)

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)

RecBaselines2023: a new dataset for choosing baselines for recommender models. - Veronika Ivanova; Oleg Lashinin; Marina Ananyeva; Sergey Kolesnikov (BIR@ECIR, 2023)

Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations. - Denis Krasilnikov; Oleg Lashinin; Maksim Tsygankov; Marina Ananyeva; Sergey Kolesnikov (CSW@WSDM, 2023)

Time-Dependent Next-Basket Recommendations. - Sergey Naumov; Marina Ananyeva; Oleg Lashinin; Sergey Kolesnikov; Dmitry I. Ignatov (ECIR (2), 2023)

Anti-Exploration by Random Network Distillation. - Alexander Nikulin; Vladislav Kurenkov; Denis Tarasov; Sergey Kolesnikov (ICML, 2023)

GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram. - Oleg Lashinin; Kirill Bykov; Marina Ananyeva; Sergey Kolesnikov (KaRS@RecSys, 2023)

Katakomba: Tools and Benchmarks for Data-Driven NetHack. - Vladislav Kurenkov; Alexander Nikulin; Denis Tarasov; Sergey Kolesnikov (NeurIPS, 2023)

Revisiting the Minimalist Approach to Offline Reinforcement Learning. - Denis Tarasov; Vladislav Kurenkov; Alexander Nikulin; Sergey Kolesnikov (NeurIPS, 2023)

CORL: Research-oriented Deep Offline Reinforcement Learning Library. - Denis Tarasov; Alexander Nikulin; Dmitry Akimov; Vladislav Kurenkov; Sergey Kolesnikov (NeurIPS, 2023)

Next-basket Recommendation Constrained by Total Cost. - Denis Krasilnikov; Oleg Lashinin; Marina Ananyeva; Sergey Kolesnikov (ORSUM@RecSys, 2023)

Time-Aware Item Weighting for the Next Basket Recommendations. - Aleksey Romanov; Oleg Lashinin; Marina Ananyeva; Sergey Kolesnikov (RecSys, 2023)

Make your next item recommendation model time sensitive. - Elizaveta Makhneva; Anna Sverkunova; Oleg Lashinin; Marina Ananyeva; Sergey Kolesnikov (UMAP (Adjunct Publication), 2023)

Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy. - Stanislav Dereka; Ivan Karpukhin; Sergey Kolesnikov (CoRR, 2023)

Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression. - Sergey Kolesnikov (CoRR, 2023)

Unveiling Empirical Pathologies of Laplace Approximation for Uncertainty Estimation. - Maksim Zhdanov 002; Stanislav Dereka; Sergey Kolesnikov (CoRR, 2023)

Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy. - Stanislav Dereka; Ivan Karpukhin; Maksim Zhdanov 002; Sergey Kolesnikov (ICIP, 2024)

In-Context Reinforcement Learning for Variable Action Spaces. - Viacheslav Sinii; Alexander Nikulin; Vladislav Kurenkov; Ilya Zisman; Sergey Kolesnikov (ICML, 2024)

Emergence of In-Context Reinforcement Learning from Noise Distillation. - Ilya Zisman; Vladislav Kurenkov; Alexander Nikulin; Viacheslav Sinii; Sergey Kolesnikov (ICML, 2024)

XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX. - Alexander Nikulin; Vladislav Kurenkov; Ilya Zisman; Artem Agarkov; Viacheslav Sinii; Sergey Kolesnikov (NeurIPS, 2024)

Revisiting BPR: A Replicability Study of a Common Recommender System Baseline. - Aleksandr Milogradskii; Oleg Lashinin; Alexander P; Marina Ananyeva; Sergey Kolesnikov (RecSys, 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)

EXACT: How to train your accuracy. - Ivan Karpukhin; Stanislav Dereka; Sergey Kolesnikov (Pattern Recognit. Lett., 2024)

Probabilistic embeddings revisited. - Ivan Karpukhin; Stanislav Dereka; Sergey Kolesnikov (Vis. Comput., 2024)

Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection. - Maksim Zhdanov 002; Stanislav Dereka; Sergey Kolesnikov (WACV, 2025)