| Microtubules govern stress granule mobility and dynamics ES Nadezhdina, AJ Lomakin, AA Shpilman, EM Chudinova, PA Ivanov Biochimica et Biophysica Acta (BBA)-Molecular Cell Research 1803 (3), 361-371, 2010 | 134 | 2010 |
| Deep Multi-Agent Reinforcement Learning with Relevance Graphs A Malysheva, TT Sung, CB Sohn, D Kudenko, A Shpilman NIPS 2018 Deep RL Workshop, 2018 | 52 | 2018 |
| Artificial Intelligence for Prosthetics: Challenge Solutions Ł Kidziński, C Ong, SP Mohanty, J Hicks, SF Carroll, B Zhou, H Zeng, ... The NeurIPS '18 Competition, 69-128, 2019 | 43 | 2019 |
| Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World F Laurent, M Schneider, C Scheller, J Watson, J Li, Z Chen, Y Zheng, ... NeurIPS 2020 Competition and Demonstration Track, 275-301, 2021 | 25 | 2021 |
| MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning A Malysheva, D Kudenko, A Shpilman 2019 XVI International Symposium" Problems of Redundancy in Information and …, 2019 | 22 | 2019 |
| Minerl diamond 2021 competition: Overview, results, and lessons learned A Kanervisto, S Milani, K Ramanauskas, N Topin, Z Lin, J Li, J Shi, D Ye, ... NeurIPS 2021 Competitions and Demonstrations Track, 13-28, 2022 | 21 | 2022 |
| Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation I Sosin, D Kudenko, A Shpilman 2018 15th International Conference on Control, Automation, Robotics and …, 2018 | 20 | 2018 |
| Scalable Multi-Agent Model-Based Reinforcement Learning V Egorov, A Shpilman Proceedings of the 21st International Conference on Autonomous Agents and …, 2022 | 13 | 2022 |
| Solving black-box optimization challenge via learning search space partition for local bayesian optimization M Sazanovich, A Nikolskaya, Y Belousov, A Shpilman NeurIPS 2020 Competition and Demonstration Track, 77-85, 2021 | 13 | 2021 |
| Traffic4cast at NeurIPS 2021-Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes C Eichenberger, M Neun, H Martin, P Herruzo, M Spanring, Y Lu, S Choi, ... NeurIPS 2021 Competitions and Demonstrations Track, 97-112, 2022 | 12 | 2022 |
| Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler T Bryksin, V Petukhov, I Alexin, S Prikhodko, A Shpilman, V Kovalenko, ... Proceedings of the 17th International Conference on Mining Software …, 2020 | 11 | 2020 |
| Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation N Lukashina, A Alenicheva, E Vlasova, A Kondiukov, A Khakimova, ... NeurIPS'2020 Machine Learning for Molecules Workshop, 2020 | 10 | 2020 |
| Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks A Shpilman, D Boikiy, M Polyakova, D Kudenko, A Burakov, ... 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 10 | 2017 |
| A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds A Gaydashenko, D Kudenko, A Shpilman 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 9 | 2018 |
| Practical AI Cases for Solving ESG Challenges E Burnaev, E Mironov, A Shpilman, M Mironenko, D Katalevsky Sustainability 15 (17), 12731, 2023 | 8 | 2023 |
| Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting T Grigoryev, P Verezemskaya, M Krinitskiy, N Anikin, A Gavrikov, ... Remote Sensing 14 (22), 5837, 2022 | 8 | 2022 |
| Self-Imitation Learning from Demonstrations G Pshikhachev, D Ivanov, V Egorov, A Shpilman NeurIPS'2021 Deep Reinforcement Learning Workshop, 2021 | 8 | 2021 |
| Automatic generation of reviews of scientific papers A Nikiforovskaya, N Kapralov, A Vlasova, O Shpynov, A Shpilman 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 8 | 2020 |
| Disturbance of the radial system of interphase microtubules in the presence of excess serum in cell culture medium EV Usova, AV Burakov, AA Shpilman, ES Nadezhdina Biophysics 53 (6), 523-526, 2008 | 7* | 2008 |
| Automatic recommendation of move method refactorings using clustering ensembles T Bryksin, E Novozhilov, A Shpilman Proceedings of the 2nd International Workshop on Refactoring, 42-45, 2018 | 6 | 2018 |
