Jayakumar Subramanian

Orcid: 0000-0003-4621-2677

According to our database1, Jayakumar Subramanian authored at least 19 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
Robustness and Sample Complexity of Model-Based MARL for General-Sum Markov Games.
Dyn. Games Appl., March, 2023

Behavior Optimized Image Generation.
CoRR, 2023

Mean-field games among teams.
CoRR, 2023

Counterfactual Explanation Policies in RL.
CoRR, 2023

SARC: Soft Actor Retrospective Critic.
CoRR, 2023

Explaining RL Decisions with Trajectories.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Differentiable Agent-based Epidemiology.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems.
J. Mach. Learn. Res., 2022

Differentiable Agent-based Epidemiology.
CoRR, 2022

Status-quo Policy Gradient in Multi-Agent Reinforcement Learning.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks.
CoRR, 2021

DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions.
Proceedings of the Winter Simulation Conference, 2021

Medical Dead-ends and Learning to Identify High-Risk States and Treatments.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Renewal Monte Carlo: Renewal Theory-Based Reinforcement Learning.
IEEE Trans. Autom. Control., 2020

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare.
Proceedings of the Machine Learning for Health Workshop, 2020

2019
Approximate information state for partially observed systems.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Reinforcement Learning in Stationary Mean-field Games.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
On Controllability of Leader-Follower Dynamics over a Directed Graph.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Stochastic approximation based methods for computing the optimal thresholds in remote-state estimation with packet drops.
Proceedings of the 2017 American Control Conference, 2017


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