Jayesh K. Gupta

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 53

Top Topics

Clifford Algebra

Reinforcement Learning

Top Venues

Publications

Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera Ojeda, Sai Vemprala, Rogerio Bonatti, Kostas Daniilidis, Ashish Kapoor, Vijay Kumar, Nikolai Matni, Jayesh K. Gupta
EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields. WACV (2024)
Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Anna Vaughan, Jayesh K. Gupta, Kit Thambiratnam, Alex Archibald, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris
Aurora: A Foundation Model of the Atmosphere. CoRR (2024)
Jayesh K. Gupta, Johannes Brandstetter
Towards Multi-spatiotemporal-scale Generalized PDE Modeling. Trans. Mach. Learn. Res. 2023 (2023)
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover
ClimaX: A foundation model for weather and climate. CoRR (2023)
Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta
Clifford Neural Layers for PDE Modeling. ICLR (2023)
David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter
Geometric Clifford Algebra Networks. CoRR (2023)
Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera Ojeda, Sai Vemprala, Rogerio Bonatti, Kostas Daniilidis, Ashish Kapoor, Vijay Kumar, Nikolai Matni, Jayesh K. Gupta
EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields. CoRR (2023)
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover
ClimaX: A foundation model for weather and climate. ICML (2023)
David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter
Geometric Clifford Algebra Networks. ICML (2023)
Jayesh K. Gupta, Sai Vemprala, Ashish Kapoor
Learning Modular Simulations for Homogeneous Systems. CoRR (2022)
Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. AAAI (2022)
Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. AAMAS (2022)
Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta
Clifford Neural Layers for PDE Modeling. CoRR (2022)
Benoît Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor
Learning to Simulate Realistic LiDARs. CoRR (2022)
Jayesh K. Gupta, Sai Vemprala, Ashish Kapoor
Learning Modular Simulations for Homogeneous Systems. NeurIPS (2022)
Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. CoRR (2022)
Jayesh K. Gupta, Johannes Brandstetter
Towards Multi-spatiotemporal-scale Generalized PDE Modeling. CoRR (2022)
Benoît Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor
Learning to Simulate Realistic LiDARs. IROS (2022)
Shuang Ma, Sai Vemprala, Wenshan Wang, Jayesh K. Gupta, Yale Song, Daniel McDuff, Ashish Kapoor
COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems. IROS (2022)
Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer
Scalable Anytime Planning for Multi-Agent MDPs (Extended Abstract). IJCAI (2022)
Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. CoRR (2022)
Shuang Ma, Sai Vemprala, Wenshan Wang, Jayesh K. Gupta, Yale Song, Daniel McDuff, Ashish Kapoor
COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems. CoRR (2022)
Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg
Dynamic multi-robot task allocation under uncertainty and temporal constraints. Auton. Robots 46 (1) (2022)
Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer
Scalable Online Planning for Multi-Agent MDPs. J. Artif. Intell. Res. 73 (2022)
Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. AAMAS (2021)
Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer
Scalable Anytime Planning for Multi-Agent MDPs. CoRR (2021)
Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer
Scalable Anytime Planning for Multi-Agent MDPs. AAMAS (2021)
Kunal Menda, Jayesh K. Gupta, Zachary Manchester, Mykel J. Kochenderfer
Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual. CoRR (2021)
Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM. ICML (2020)
Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer
Normalizing Flow Policies for Multi-agent Systems. GameSec (2020)
Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. CoRR (2020)
Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. Robotics: Science and Systems (2020)
Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer
Normalizing Flow Model for Policy Representation in Continuous Action Multi-agent Systems. AAMAS (2020)
Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer
Model primitives for hierarchical lifelong reinforcement learning. Auton. Agents Multi Agent Syst. 34 (1) (2020)
Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM. CoRR (2020)
Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. CoRR (2020)
Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer
Structured Mechanical Models for Robot Learning and Control. L4DC (2020)
Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer
Structured Mechanical Models for Robot Learning and Control. CoRR (2020)
Raunak P. Bhattacharyya, Derek J. Phillips, Changliu Liu, Jayesh K. Gupta, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer
Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning. CoRR (2019)
Ross E. Allen, Javona White Bear, Jayesh K. Gupta, Mykel J. Kochenderfer
Health-Informed Policy Gradients for Multi-Agent Reinforcement Learning. CoRR (2019)
Raunak P. Bhattacharyya, Derek J. Phillips, Changliu Liu, Jayesh K. Gupta, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer
Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning. ICRA (2019)
Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer
Model Primitive Hierarchical Lifelong Reinforcement Learning. AAMAS (2019)
Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer
A General Framework for Structured Learning of Mechanical Systems. CoRR (2019)
Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer
Model Primitive Hierarchical Lifelong Reinforcement Learning. CoRR (2019)
Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards
Learning Policy Representations in Multiagent Systems. CoRR (2018)
John Mern, Jayesh K. Gupta, Mykel J. Kochenderfer
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures. CoRR (2018)
Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards
Learning Policy Representations in Multiagent Systems. ICML (2018)
Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards
Evaluating Generalization in Multiagent Systems using Agent-Interaction Graphs. AAMAS (2018)
Jayesh K. Gupta, Maxim Egorov, Mykel J. Kochenderfer
Cooperative Multi-agent Control Using Deep Reinforcement Learning. AAMAS Workshops (Selected Papers) (2017)
John Mern, Jayesh K. Gupta, Mykel J. Kochenderfer
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures. SSCI (2017)
Maxim Egorov, Zachary N. Sunberg, Edward Balaban, Tim Allan Wheeler, Jayesh K. Gupta, Mykel J. Kochenderfer
POMDPs.jl: A Framework for Sequential Decision Making under Uncertainty. J. Mach. Learn. Res. 18 (2017)
Jonathan Ho, Jayesh K. Gupta, Stefano Ermon
Model-Free Imitation Learning with Policy Optimization. ICML (2016)
Jonathan Ho, Jayesh K. Gupta, Stefano Ermon
Model-Free Imitation Learning with Policy Optimization. CoRR (2016)
Ashesh Jain, Debarghya Das, Jayesh K. Gupta, Ashutosh Saxena
PlanIt: A crowdsourcing approach for learning to plan paths from large scale preference feedback. ICRA (2015)