Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks. - Aleksei Shpilman; Dmitry Boikiy; Marina Polyakova; Daniel Kudenko; Anton Burakov; Elena Nadezhdina (ICMLA, 2017)

Automated Refactoring of Object-Oriented Code Using Clustering Ensembles. - Timofey Bryksin; Alexey Shpilman; Daniel Kudenko (AAAI Workshops, 2018)

Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. - Aleksandra Malysheva; Daniel Kudenko; Aleksei Shpilman (ICARCV, 2018)

Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. - Ivan Sosin; Daniel Kudenko; Aleksei Shpilman (ICARCV, 2018)

A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds. - Anastasia Gaydashenko; Daniel Kudenko; Aleksei Shpilman (ICMLA, 2018)

Automatic recommendation of move method refactorings using clustering ensembles. - Timofey Bryksin; Evgenii Novozhilov; Aleksei Shpilman (IWoR@ASE, 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 Classification of Error Types in Solutions to Programming Assignments at Online Learning Platform. - Artyom Lobanov; Timofey Bryksin; Alexey Shpilman (AIED (2), 2019)

End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box. - Vladislav Belyaev; Aleksandra Malysheva; Aleksei Shpilman (REDUNDANCY, 2019)

MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. - Aleksandra Malysheva; Daniel Kudenko; Aleksei Shpilman (REDUNDANCY, 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 021; Rongzhong Lian; Hao Tian 005; Wojciech Jaskowski; Garrett Andersen; et al. (CoRR, 2019)

Automatic generation of reviews of scientific papers. - Anna Nikiforovskaya; Nikolai Kapralov; Anna Vlasova; Oleg Shpynov; Aleksei Shpilman (ICMLA, 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 (MSR, 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 001; Zhe Chen 016; Yi Zheng; Shao-Hung Chan; Konstantin Makhnev; Oleg Svidchenko; Vladimir Egorov; Dmitry Ivanov; et al. (NeurIPS (Competition and Demos), 2020)

Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization. - Mikita Sazanovich; Anastasiya Nikolskaya; Yury Belousov 001; Aleksei Shpilman (NeurIPS (Competition and Demos), 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)

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)

Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments. - Dmitry Ivanov; Vladimir Egorov; Aleksei Shpilman (AAMAS, 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; et al. (NeurIPS (Competition and Demos), 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 016; Wei Yang 032; Weijun Hong; Zhongyue Huang; et al. (NeurIPS (Competition and Demos), 2021)

Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation. - Vsevolod Konyakhin; Nina Lukashina; 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)

Maximum Entropy Model-based Reinforcement Learning. - Oleg Svidchenko; Aleksei Shpilman (CoRR, 2021)

Scalable Multi-Agent Model-Based Reinforcement Learning. - Vladimir Egorov; Alexey Shpilman (AAMAS, 2022)

Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data. - Farid Bagirov; Dmitry Ivanov; Aleksei Shpilman (CoRR, 2022)

Self-Imitation Learning from Demonstrations. - Georgiy Pshikhachev; Dmitry Ivanov; Vladimir Egorov; Aleksei Shpilman (CoRR, 2022)

SimVec: predicting polypharmacy side effects for new drugs. - Nina Lukashina; Elena Kartysheva; Ola Spjuth; Elizaveta Virko; Aleksei Shpilman (J. Cheminformatics, 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)

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 (CEC, 2023)

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems. - Stepan Kulibaba; Artem Dzhalilov; Roman Pakhomov; Oleg Svidchenko; Alexander Gasnikov; Aleksei Shpilman (CoRR, 2025)