Aleksei Shpilman

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 39

Top Topics

Clustering Ensemble

Maximum Entropy

Reinforcement Learning

Top Venues

NeurIPS (Competition and Demos)

Publications

Anastasiia Filatova, Mikhail Kovalchuk, Stanislav Batalenkov, Aleksander Voskresenskiy, Irina Deeva, Anna V. Kaluzhnaya, Aleksei Shpilman, Natalia Kondrashova, Maxim Dudnichenko, Denis Nasonov
A Multi-Contractor Approach for MLRCPSP with the Graph Structure Optimization. CEC (2023)
Timofey Grigoryev, Polina Verezemskaya, Mikhail Krinitskiy, Nikita Anikin, Alexander Gavrikov, Ilya Trofimov, Nikita Balabin, Aleksei Shpilman, Andrei Eremchenko, Sergey Gulev, Evgeny Burnaev, Vladimir Vanovskiy
Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting. Remote. Sens. 14 (22) (2022)
Timofey Grigoryev, Polina Verezemskaya, Mikhail Krinitskiy, Nikita Anikin, Alexander Gavrikov, Ilya Trofimov, Nikita Balabin, Aleksei Shpilman, Andrei Eremchenko, Sergey Gulev, Evgeny Burnaev, Vladimir Vanovskiy
Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting. CoRR (2022)
Farid Bagirov, Dmitry Ivanov, Aleksei Shpilman
Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data. 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)
Vladimir Egorov, Aleksei Shpilman
Scalable Multi-Agent Model-Based Reinforcement Learning. CoRR (2022)
Georgiy Pshikhachev, Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman
Self-Imitation Learning from Demonstrations. CoRR (2022)
Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Jay Santokhi, Dylan Hillier, Yiming Yang, Joned Sarwar, Anna Jordan, Emil Hewage, David Jonietz, Fei Tang, Aleksandra Gruca, Michael Kopp, David P. Kreil, Sepp Hochreiter
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. CoRR (2022)
Nina Lukashina, Elena Kartysheva, Ola Spjuth, Elizaveta Virko, Aleksei Shpilman
SimVec: predicting polypharmacy side effects for new drugs. J. Cheminformatics 14 (1) (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)
Natalia Zenkova, Ekaterina Sedykh, Tatiana Shugaeva, Vladislav Strashko, Timofei Ermak, Aleksei Shpilman
Simple End-to-end Deep Learning Model for CDR-H3 Loop Structure Prediction. CoRR (2021)
Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman
Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation. CoRR (2021)
Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman
Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments. CoRR (2021)
Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman
Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments. AAMAS (2021)
Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy D. Watson, Jiaoyang Li, Zhe Chen, Yi Zheng, Shao-Hung Chan, Konstantin Makhnev, Oleg Svidchenko, Vladimir Egorov, Dmitry Ivanov, Aleksei Shpilman, Evgenija Spirovska, Oliver Tanevski, Aleksandar Nikov, Ramon Grunder, David Galevski, Jakov Mitrovski, Guillaume Sartoretti, Zhiyao Luo, Mehul Damani, Nilabha Bhattacharya, Shivam Agarwal, Adrian Egli, Erik Nygren, Sharada P. Mohanty
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World. CoRR (2021)
Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Jay Santokhi, Dylan Hillier, Yiming Yang, Joned Sarwar, Anna Jordan, Emil Hewage, David Jonietz, Fei Tang, Aleksandra Gruca, Michael Kopp, David P. Kreil, Sepp Hochreiter
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. NeurIPS (Competition and Demos) (2021)
Oleg Svidchenko, Aleksei Shpilman
Maximum Entropy Model-based Reinforcement Learning. CoRR (2021)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. CoRR (2020)
Anna Nikiforovskaya, Nikolai Kapralov, Anna Vlasova, Oleg Shpynov, Aleksei Shpilman
Automatic generation of reviews of scientific papers. ICMLA (2020)
Mikita Sazanovich, Anastasiya Nikolskaya, Yury Belousov, Aleksei Shpilman
Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization. CoRR (2020)
Mikita Sazanovich, Konstantin Chaika, Kirill Krinkin, Aleksei Shpilman
Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously. CoRR (2020)
Mikita Sazanovich, Anastasiya Nikolskaya, Yury Belousov, Aleksei Shpilman
Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization. NeurIPS (Competition and Demos) (2020)
Nina Lukashina, Alisa Alenicheva, Elizaveta Vlasova, Artem Kondiukov, Aigul Khakimova, Emil Magerramov, Nikita Churikov, Aleksei Shpilman
Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation. CoRR (2020)
Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman
End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box. CoRR (2020)
Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman
A comparative evaluation of machine learning methods for robot navigation through human crowds. CoRR (2020)
Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina
Deep Learning of Cell Classification using Microscope Images of Intracellular Microtubule Networks. CoRR (2020)
Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy D. Watson, Jiaoyang Li, Zhe Chen, Yi Zheng, Shao-Hung Chan, Konstantin Makhnev, Oleg Svidchenko, Vladimir Egorov, Dmitry Ivanov, Aleksei Shpilman, Evgenija Spirovska, Oliver Tanevski, Aleksandar Nikov, Ramon Grunder, David Galevski, Jakov Mitrovski, Guillaume Sartoretti, Zhiyao Luo, Mehul Damani, Nilabha Bhattacharya, Shivam Agarwal, Adrian Egli, Erik Nygren, Sharada P. Mohanty
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World. NeurIPS (Competition and Demos) (2020)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. CoRR (2020)
Anna Nikiforovskaya, Nikolai Kapralov, Anna Vlasova, Oleg Shpynov, Aleksei Shpilman
Automatic generation of reviews of scientific papers. CoRR (2020)
Ivan Sosin, Daniel Kudenko, Aleksei Shpilman
Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. CoRR (2020)
Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hong-cheng 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
Artificial Intelligence for Prosthetics - challenge solutions. CoRR (2019)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. REDUNDANCY (2019)
Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman
End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box. REDUNDANCY (2019)
Timofey Bryksin, Evgenii Novozhilov, Aleksei Shpilman
Automatic recommendation of move method refactorings using clustering ensembles. IWoR@ASE (2018)
Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman
A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds. ICMLA (2018)
Aleksandra Malysheva, Tegg Tae Kyong Sung, Chae-Bong Sohn, Daniel Kudenko, Aleksei Shpilman
Deep Multi-Agent Reinforcement Learning with Relevance Graphs. CoRR (2018)
Ivan Sosin, Daniel Kudenko, Aleksei Shpilman
Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. ICARCV (2018)
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. ICARCV (2018)
Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina
Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks. ICMLA (2017)