Jayakumar Subramanian
Jayakumar Subramanian
Senior Research Scientist, Adobe India
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Cited by
Cited by
Reinforcement Learning in Stationary Mean-field Games
J Subramanian, A Mahajan
Proceedings of the 18th International Conference on Autonomous Agents and …, 2019
Public health impact of delaying second dose of BNT162b2 or mRNA-1273 covid-19 vaccine: simulation agent based modeling study
S Romero-Brufau, A Chopra, AJ Ryu, E Gel, R Raskar, W Kremers, ...
bmj 373, 2021
Approximate information state for approximate planning and reinforcement learning in partially observed systems
J Subramanian, A Sinha, R Seraj, A Mahajan
Journal of Machine Learning Research 23 (12), 1-83, 2022
On the link between weighted least-squares and limiters used in higher-order reconstructions for finite volume computations of hyperbolic equations
JC Mandal, J Subramanian
Applied Numerical Mathematics 58 (5), 705-725, 2008
Medical dead-ends and learning to identify high-risk states and treatments
M Fatemi, TW Killian, J Subramanian, M Ghassemi
Advances in Neural Information Processing Systems 34, 4856-4870, 2021
Approximate information state for partially observed systems
J Subramanian, A Mahajan
Reinforcement Learning and Decision Making (RLDM), Montreal, July 7-10, 2019, 2019
An empirical study of representation learning for reinforcement learning in healthcare
MG Taylor W Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi
Machine Learning for Health NeurIPS Workshop, PMLR 136, 139-160, 2020
Transient aero-thermal mapping of passive Thermal Protection system for nose-cap of Reusable Hypersonic Vehicle
SP Mahulikar, S Khurana, R Dungarwal, SG Shevakari, J Subramanian, ...
The Journal of the Astronautical Sciences 56 (4), 593-619, 2008
Differentiable Agent-based Epidemiology
A Chopra, A Rodríguez, J Subramanian, B Krishnamurthy, BA Prakash, ...
arXiv preprint arXiv:2207.09714, 2022
Renewal Monte Carlo: Renewal theory based reinforcement learning
J Subramanian, A Mahajan
Proceedings of the IEEE Conference on Decision and Control (CDC), Miami, Florida, 2018
Stochastic approximation based methods for computing the optimal thresholds in remote-state estimation with packet drops
J Chakravorty, J Subramanian, A Mahajan
American Control Conference (ACC), 2017, 462-467, 2017
Robustness and sample complexity of model-based MARL for general-sum Markov games
J Subramanian, A Sinha, A Mahajan
arXiv preprint arXiv:2110.02355, 2021
Reinforcement learning for mean-field teams
J Subramanian, R Seraj, A Mahajan
Reinforcement Learning and Decision Making (RLDM), Montreal, July 7-10, 2019, 2019
Reinforcement Learning for Mean-field Teams
J Subramanian, R Seraj, A Mahajan
AAMAS Workshop on Adaptive and Learning Agents, 2019
High‐resolution finite volume computations using a novel weighted least‐squares formulation
JC Mandal, S Rao, J Subramanian
International journal for numerical methods in fluids 56 (8), 1425-1431, 2008
DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks-a Case Study For Covid-19 Spread and Interventions
A Chopra, R Raskar, J Subramanian, B Krishnamurthy, ES Gel, ...
2021 Winter Simulation Conference (WSC), 1-12, 2021
Inducing Cooperative behaviour in Sequential-Social dilemmas through Multi-Agent Reinforcement Learning using Status-Quo Loss
P Badjatiya, M Sarkar, A Sinha, S Singh, N Puri, J Subramanian, ...
arXiv preprint arXiv:2001.05458, 2020
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks
A Chopra, E Gel, J Subramanian, B Krishnamurthy, S Romero-Brufau, ...
arXiv preprint arXiv:2110.04421, 2021
A policy gradient algorithm to compute boundedly rational stationary mean field equilibria
J Subramanian, A Mahajan
Proceedings of the ICML/IJCAI/AAMAS Workshop on Planning and Learning (PAL …, 2018
Explaining RL Decisions with Trajectories
SV Deshmukh, A Dasgupta, C Agarwal, N Jiang, B Krishnamurthy, ...
International Conference on Learning Representations, 0
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