AI Labs
Publications
Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data
March 2022
Farid Bagirov, Dmitry Ivanov, Aleksei Shpilman
Maximum Entropy Model-based Reinforcement Learning
December 2021
Oleg Svidchenko, Aleksei Shpilman
Self-Imitation Learning from Demonstrations
December 2021
Georgiy Pshikhachev, Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman
Simple End-to-end Deep Learning Model for CDR-H3 Loop Structure Prediction
December 2021
Natalia Zenkova, Ekaterina Sedykh, Tatiana Shugaeva, Vladislav Strashko, Timofei Ermak, Aleksei Shpilman
Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation
November 2021
Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman
Integrating Statistical and Machine-Learning Approach for Meta-Analysis of Bisphenol A-Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
October 2021
Lukashina, N.; Williams, M.J.; Kartysheva, E.; Virko, E.; Kudłak, B.; Fredriksson, R.; Spjuth, O.; Schiöth, H.B.
Solving black-box optimization challenge via learning search space partition for local bayesian optimization
August 2021
Mikita Sazanovich, Anastasiya Nikolskaya, Yury Belousov, Aleksei Shpilman
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World
March 2021
Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy 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 Mohanty
Automatic generation of reviews of scientific papers
December 2020
Anna Nikiforovskaya, Nikolai Kapralov, Anna Vlasova, Oleg Shpynov, Aleksei Shpilman
Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation
December 2020
Nina Lukashina, Alisa Alenicheva, Elizaveta Vlasova, Artem Kondiukov, Aigul Khakimova, Emil Magerramov, Nikita Churikov, Aleksei Shpilman
Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously
July 2020
Mikita Sazanovich, Konstantin Chaika, Kirill Krinkin, Aleksei Shpilman
Artificial Intelligence for Prosthetics-challenge solutions
November 2019
Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty, Jennifer Hicks, Sean F Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaśkowski, 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 Watson, Marcel Salathé, Sergey Levine, Scott Delp
MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning
October 2019
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box
October 2019
Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman
Log-based Reading Speed Prediction: a Case Study on War and Peace
July 2019
Igor Tukh, Pavel Braslavski, and Kseniya Buraya
Words and Topics: Content Representations for Book Recommendation
May 2019
Larissa Kolesnichenko, Pavel Braslavski
Deep Multi-Agent Reinforcement Learning with Relevance Graphs
December 2018
Aleksandra Malysheva, Tegg Taekyong Sung, Chae-Bong Sohn, Daniel Kudenko, Aleksei Shpilman
Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing
December 2018
Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
A comparative evaluation of machine learning methods for robot navigation through human crowds
December 2018
A. Gaydashenko, D. Kudenko, A. Shpilman
Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data
November 2018
A. Malysheva, D. Kudenko, A. Shpilman
Rainbow World Models
November 2018
V. Chockalingam, T. Sung, F. Behbahani, R. Gargeya, A. Sivanantham, A. Malysheva
Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation
November 2018
I. Sosin, D. Kudenko, A. Shpilman
Cleaning up after a Party: Post-processing Thesaurus Crowdsourced Data
October 2018
Oksana Antropova, Elena Arslanova, Maxim Shaposhnikov, Pavel Braslavski, Mikhail Mukhin
Stierlitz Meets SVM: Humor Detection in Russian
October 2018
Anton Ermilov, Natasha Murashkina, Valeria Goryacheva, Pavel Braslavski
Automatic Recommendation of Move Method Refactorings Using Clustering Ensembles
September 2018
Timofey Bryksin, Evgenii Novozhilov, and Aleksei Shpilman
Personal Names Popularity Estimation and its Application to Record Linkage
September 2018
Ksenia Zhagorina, Pavel Braslavski, Vladimir Gusev
Learning to Run with Reward Shaping from Video Data
July 2018
A. Malysheva, A. Shpilman, D. Kudenko
Building Detection from Satellite Imagery Using a Composite Loss Function
June 2018
S. Golovanov, R. Kurbanov, A. Artamonov, A. Davydow, S. Nikolenko
Automated Refactoring of Object-Oriented Code Using Clustering Ensembles
June 2018
Timofey Bryskin, Alexey Shpilman, and Daniel Kudenko
Behavioural realism and the activation of aggressive concepts in violent video games
January 2018
D. Zendle, D. Kudenko, P. Cairns
Deep Learning of Cell Classification using Microscope Images of Intracellular Microtubule Networks
December 2017
A. Shpilman, D. Boikiy, M. Plyakova, D. Kudenko, A. Burakov, E. Nadezhdina