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Jayesh K. Gupta
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2020 – today
- 2024
- [c25]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: 5834-5843 - [i24]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 abs/2405.13063 (2024) - 2023
- [j5]Jayesh K. Gupta, Johannes Brandstetter:
Towards Multi-spatiotemporal-scale Generalized PDE Modeling. Trans. Mach. Learn. Res. 2023 (2023) - [c24]Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta:
Clifford Neural Layers for PDE Modeling. ICLR 2023 - [c23]Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover:
ClimaX: A foundation model for weather and climate. ICML 2023: 25904-25938 - [c22]David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter:
Geometric Clifford Algebra Networks. ICML 2023: 29306-29337 - [i23]Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover:
ClimaX: A foundation model for weather and climate. CoRR abs/2301.10343 (2023) - [i22]David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter:
Geometric Clifford Algebra Networks. CoRR abs/2302.06594 (2023) - [i21]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 abs/2310.02437 (2023) - 2022
- [j4]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): 231-247 (2022) - [j3]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Online Planning for Multi-Agent MDPs. J. Artif. Intell. Res. 73: 821-846 (2022) - [c21]Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer:
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. AAAI 2022: 7664-7671 - [c20]Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer:
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. AAMAS 2022: 1723-1725 - [c19]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs (Extended Abstract). IJCAI 2022: 5279-5283 - [c18]Shuang Ma, Sai Vemprala, Wenshan Wang, Jayesh K. Gupta, Yale Song, Daniel McDuff, Ashish Kapoor:
COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems. IROS 2022: 1000-1007 - [c17]Benoît Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor:
Learning to Simulate Realistic LiDARs. IROS 2022: 8173-8180 - [c16]Jayesh K. Gupta, Sai Vemprala, Ashish Kapoor:
Learning Modular Simulations for Homogeneous Systems. NeurIPS 2022 - [i20]Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer:
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. CoRR abs/2203.02844 (2022) - [i19]Shuang Ma, Sai Vemprala, Wenshan Wang, Jayesh K. Gupta, Yale Song, Daniel McDuff, Ashish Kapoor:
COMPASS: Contrastive Multimodal Pretraining for Autonomous Systems. CoRR abs/2203.15788 (2022) - [i18]Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta:
Clifford Neural Layers for PDE Modeling. CoRR abs/2209.04934 (2022) - [i17]Benoît Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor:
Learning to Simulate Realistic LiDARs. CoRR abs/2209.10986 (2022) - [i16]Jayesh K. Gupta, Johannes Brandstetter:
Towards Multi-spatiotemporal-scale Generalized PDE Modeling. CoRR abs/2209.15616 (2022) - [i15]Jayesh K. Gupta, Sai Vemprala, Ashish Kapoor:
Learning Modular Simulations for Homogeneous Systems. CoRR abs/2210.16294 (2022) - [i14]Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer:
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. CoRR abs/2210.17540 (2022) - 2021
- [c15]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs. AAMAS 2021: 341-349 - [c14]Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer:
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. AAMAS 2021: 764-772 - [i13]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs. CoRR abs/2101.04788 (2021) - [i12]Kunal Menda, Jayesh K. Gupta, Zachary Manchester, Mykel J. Kochenderfer:
Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual. CoRR abs/2105.01811 (2021) - 2020
- [b1]Jayesh K. Gupta:
Modularity and coordination for planning and reinforcement learning. Stanford University, USA, 2020 - [j2]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model primitives for hierarchical lifelong reinforcement learning. Auton. Agents Multi Agent Syst. 34(1): 28 (2020) - [c13]Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer:
Normalizing Flow Model for Policy Representation in Continuous Action Multi-agent Systems. AAMAS 2020: 1916-1918 - [c12]Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer:
Normalizing Flow Policies for Multi-agent Systems. GameSec 2020: 277-296 - [c11]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: 6830-6840 - [c10]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
Structured Mechanical Models for Robot Learning and Control. L4DC 2020: 328-337 - [c9]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 - [d1]Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel John Kochenderfer, Zachary Manchester:
Normalized Stanford Helicopter Dataset. Zenodo, 2020 - [i11]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
Structured Mechanical Models for Robot Learning and Control. CoRR abs/2004.10301 (2020) - [i10]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. CoRR abs/2005.13109 (2020) - [i9]Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer:
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. CoRR abs/2006.11438 (2020) - [i8]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 abs/2006.11615 (2020)
2010 – 2019
- 2019
- [c8]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model Primitive Hierarchical Lifelong Reinforcement Learning. AAMAS 2019: 34-42 - [c7]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: 789-795 - [i7]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
A General Framework for Structured Learning of Mechanical Systems. CoRR abs/1902.08705 (2019) - [i6]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model Primitive Hierarchical Lifelong Reinforcement Learning. CoRR abs/1903.01567 (2019) - [i5]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 abs/1903.05766 (2019) - [i4]Ross E. Allen, Javona White Bear, Jayesh K. Gupta, Mykel J. Kochenderfer:
Health-Informed Policy Gradients for Multi-Agent Reinforcement Learning. CoRR abs/1908.01022 (2019) - 2018
- [c6]Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards:
Evaluating Generalization in Multiagent Systems using Agent-Interaction Graphs. AAMAS 2018: 1944-1946 - [c5]Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards:
Learning Policy Representations in Multiagent Systems. ICML 2018: 1797-1806 - [i3]John Mern, Jayesh K. Gupta, Mykel J. Kochenderfer:
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures. CoRR abs/1802.06920 (2018) - [i2]Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards:
Learning Policy Representations in Multiagent Systems. CoRR abs/1806.06464 (2018) - 2017
- [j1]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: 26:1-26:5 (2017) - [c4]Jayesh K. Gupta, Maxim Egorov, Mykel J. Kochenderfer:
Cooperative Multi-agent Control Using Deep Reinforcement Learning. AAMAS Workshops (Selected Papers) 2017: 66-83 - [c3]John Mern, Jayesh K. Gupta, Mykel J. Kochenderfer:
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures. SSCI 2017: 1-8 - 2016
- [c2]Jonathan Ho, Jayesh K. Gupta, Stefano Ermon:
Model-Free Imitation Learning with Policy Optimization. ICML 2016: 2760-2769 - [i1]Jonathan Ho, Jayesh K. Gupta, Stefano Ermon:
Model-Free Imitation Learning with Policy Optimization. CoRR abs/1605.08478 (2016) - 2015
- [c1]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: 877-884
Coauthor Index
aka: Mykel John Kochenderfer
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last updated on 2024-09-13 00:41 CEST by the dblp team
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