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



Vladislav Belyaev , Aleksandra Malysheva , Aleksei Shpilman


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



Aleksandra Malysheva , Daniel Kudenko , Aleksei Shpilman

* arXiv admin note: substantial text overlap with arXiv:1811.12557 

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



Aleksandra Malysheva , Daniel Kudenko , Aleksei Shpilman


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Artificial Intelligence for Prosthetics - challenge solutions



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


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Deep Multi-Agent Reinforcement Learning with Relevance Graphs



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

* The first two authors contributed equally. Author ordering determined by coin flip over a Google Hangout. Accepted at NIPS 2018 Deep RL Workshop 

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