Jayesh K. Gupta
Jayesh K. Gupta
Microsoft
Verified email at cs.stanford.edu - Homepage
Title
Cited by
Cited by
Year
Cooperative multi-agent control using deep reinforcement learning
JK Gupta, M Egorov, M Kochenderfer
International Conference on Autonomous Agents and Multiagent Systems, 66-83, 2017
3452017
Model-Free Imitation Learning with Policy Optimization
J Ho, JK Gupta, S Ermon
International Conference on Machine Learning, 2016, 2016
732016
POMDPs.jl: A Framework for Sequential Decision Making under Uncertainty
M Egorov, ZN Sunberg, E Balaban, TA Wheeler, JK Gupta, ...
Journal of Machine Learning Research 18 (26), 1-5, 2017
592017
Learning policy representations in multiagent systems
A Grover, M Al-Shedivat, J Gupta, Y Burda, H Edwards
International conference on machine learning, 1802-1811, 2018
392018
Planit: A crowdsourcing approach for learning to plan paths from large scale preference feedback
A Jain, D Das, JK Gupta, A Saxena
2015 IEEE International Conference on Robotics and Automation (ICRA), 877-884, 2015
262015
Mtba: Matlab toolbox for biclustering analysis
JK Gupta, S Singh, NK Verma
IEEE workshop on computational intelligence: theories, applications and …, 2013
25*2013
Smartphone application for fault recognition
NK Verma, S Singh, JK Gupta, RK Sevakula, S Dixit, A Salour
2012 Sixth International Conference on Sensing Technology (ICST), 1-6, 2012
232012
Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning
RP Bhattacharyya, DJ Phillips, C Liu, JK Gupta, K Driggs-Campbell, ...
International Conference on Robotics and Automation, 2019
142019
A general framework for structured learning of mechanical systems
JK Gupta, K Menda, Z Manchester, MJ Kochenderfer
arXiv preprint arXiv:1902.08705, 2019
112019
Evaluating generalization in multiagent systems using agent-interaction graphs
A Grover, M Al-Shedivat, JK Gupta, Y Burda, H Edwards
Proceedings of the 17th International Conference on Autonomous Agents and …, 2018
9*2018
Structured mechanical models for robot learning and control
JK Gupta, K Menda, Z Manchester, M Kochenderfer
Learning for Dynamics and Control, 328-337, 2020
52020
Deep implicit coordination graphs for multi-agent reinforcement learning
S Li, JK Gupta, P Morales, R Allen, MJ Kochenderfer
arXiv preprint arXiv:2006.11438, 2020
42020
Model primitives for hierarchical lifelong reinforcement learning
B Wu, JK Gupta, M Kochenderfer
Autonomous Agents and Multi-Agent Systems 34 (1), 1-38, 2020
42020
Health-informed policy gradients for multi-agent reinforcement learning
RE Allen, JW Bear, JK Gupta, MJ Kochenderfer
arXiv preprint arXiv:1908.01022, 2019
32019
Feature level analysis
NK Verma, JK Gupta, S Singh, RK Sevakula, S Dixit, A Salour
IEEE Workshop on Computational Intelligence: Theories, Applications and …, 2013
32013
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
K Menda, J De Becdelievre, J Gupta, I Kroo, M Kochenderfer, ...
International Conference on Machine Learning, 6830-6840, 2020
12020
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints
S Choudhury, JK Gupta, MJ Kochenderfer, D Sadigh, J Bohg
arXiv preprint arXiv:2005.13109, 2020
12020
Normalizing Flow Policies for Multi-agent Systems
X Ma, JK Gupta, MJ Kochenderfer
International Conference on Decision and Game Theory for Security, 2020
12020
STRUCTURED MECHANICAL MODELS FOR EFFICIENT REINFORCEMENT LEARNING
K Menda, JK Gupta, Z Manchester, MJ Kochenderfer
Workshop on Structure and Priors in Reinforcement Learning, International …, 2019
12019
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures
J Mern, JK Gupta, MJ Kochenderfer
2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2017
12017
The system can't perform the operation now. Try again later.
Articles 1–20