Aleksei Shpilman

According to our database, Aleksei Shpilman authored at least 29 papers between 2017 and 2023.

Collaborative distances:

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

2023

A Multi-Contractor Approach for MLRCPSP with the Graph Structure Optimization.

Anastasiia Filatova, Mikhail V. Kovalchuk, Stanislav Batalenkov, Aleksander Voskresenskiy, Irina Deeva, Anna V. Kaluzhnaya, Aleksei Shpilman, Natalia Kondrashova, Maxim Dudnichenko, Denis A. Nasonov

Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022

Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting.

Timofey Grigoryev, Polina Verezemskaya, Mikhail Krinitskiy, Nikita Anikin, Alexander Gavrikov, Ilya Trofimov, Nikita Balabin, Aleksei Shpilman, Andrei Eremchenko, Sergey Gulev, Evgeny Burnaev, Vladimir Vanovskiy

Remote. Sens., 2022

SimVec: predicting polypharmacy side effects for new drugs.

Nina Lukashina, Elena Kartysheva, Ola Spjuth, Elizaveta Virko, Aleksei Shpilman

J. Cheminformatics, 2022

Self-Imitation Learning from Demonstrations.

Georgiy Pshikhachev, Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman

CoRR, 2022

Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data.

Farid Bagirov, Dmitry Ivanov, Aleksei Shpilman

CoRR, 2022

Scalable Multi-Agent Model-Based Reinforcement Learning.

Vladimir Egorov, Alexey Shpilman

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021

Maximum Entropy Model-based Reinforcement Learning.

Oleg Svidchenko, Aleksei Shpilman

CoRR, 2021

Simple End-to-end Deep Learning Model for CDR-H3 Loop Structure Prediction.

Natalia Zenkova, Ekaterina Sedykh, Tatiana Shugaeva, Vladislav Strashko, Timofei Ermak, Aleksei Shpilman

CoRR, 2021

Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation.

Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman

CoRR, 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

Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes.

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

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments.

Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation.

Nina Lukashina, Alisa Alenicheva, Elizaveta Vlasova, Artem Kondiukov, Aigul Khakimova, Emil Magerramov, Nikita Churikov, Aleksei Shpilman

CoRR, 2020

Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously.

Mikita Sazanovich, Konstantin Chaika, Kirill Krinkin, Aleksei Shpilman

CoRR, 2020

Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization.

Mikita Sazanovich, Anastasiya Nikolskaya, Yury Belousov, Aleksei Shpilman

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World.

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

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler.

Timofey Bryksin, Victor Petukhov, Ilya Alexin, Stanislav Prikhodko, Alexey Shpilman, Vladimir Kovalenko, Nikita Povarov

Proceedings of the MSR '20: 17th International Conference on Mining Software Repositories, 2020

Automatic generation of reviews of scientific papers.

Anna Nikiforovskaya, Nikolai Kapralov, Anna Vlasova, Oleg Shpynov, Aleksei Shpilman

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2019

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, 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

CoRR, 2019

MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning.

Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman

Proceedings of the XVI International Symposium "Problems of Redundancy in Information and Control Systems", 2019

End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box.

Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman

Proceedings of the XVI International Symposium "Problems of Redundancy in Information and Control Systems", 2019

Automatic Classification of Error Types in Solutions to Programming Assignments at Online Learning Platform.

Artyom Lobanov, Timofey Bryksin, Alexey Shpilman

Proceedings of the Artificial Intelligence in Education - 20th International Conference, 2019

2018

Deep Multi-Agent Reinforcement Learning with Relevance Graphs.

Aleksandra Malysheva, Tegg Tae Kyong Sung, Chae-Bong Sohn, Daniel Kudenko, Aleksei Shpilman

CoRR, 2018

Automatic recommendation of move method refactorings using clustering ensembles.

Timofey Bryksin, Evgenii Novozhilov, Aleksei Shpilman

Proceedings of the 2nd International Workshop on Refactoring, 2018

A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds.

Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation.

Ivan Sosin, Daniel Kudenko, Aleksei Shpilman

Proceedings of the 15th International Conference on Control, 2018

Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data.

Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman

Proceedings of the 15th International Conference on Control, 2018

Automated Refactoring of Object-Oriented Code Using Clustering Ensembles.

Timofey Bryksin, Alexey Shpilman, Daniel Kudenko

Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks.

Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina

Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017