Stochastic approximation based methods for computing the optimal thresholds in remote-state estimation with packet drops. - Jhelum Chakravorty; Jayakumar Subramanian; Aditya Mahajan (ACC, 2017)

On Controllability of Leader-Follower Dynamics over a Directed Graph. - Jayakumar Subramanian; Aditya Mahajan; Aditya A. Paranjape (CDC, 2018)

Reinforcement Learning in Stationary Mean-field Games. - Jayakumar Subramanian; Aditya Mahajan (AAMAS, 2019)

Approximate information state for partially observed systems. - Jayakumar Subramanian; Aditya Mahajan (CDC, 2019)

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. - Taylor W. Killian; Haoran Zhang 003; Jayakumar Subramanian; Mehdi Fatemi; Marzyeh Ghassemi (ML4H@NeurIPS, 2020)

Renewal Monte Carlo: Renewal Theory-Based Reinforcement Learning. - Jayakumar Subramanian; Aditya Mahajan (IEEE Trans. Autom. Control., 2020)

Medical Dead-ends and Learning to Identify High-Risk States and Treatments. - Mehdi Fatemi; Taylor W. Killian; Jayakumar Subramanian; Marzyeh Ghassemi (NeurIPS, 2021)

DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks - a Case Study For Covid-19 Spread and Interventions. - Ayush Chopra; Ramesh Raskar; Jayakumar Subramanian; Balaji Krishnamurthy; Esma Senturk Gel; Santiago Romero-Brufau; Kalyan S. Pasupathy; Thomas C. Kingsley (WSC, 2021)

DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks. - Ayush Chopra; Esma Senturk Gel; Jayakumar Subramanian; Balaji Krishnamurthy; Santiago Romero-Brufau; Kalyan S. Pasupathy; Thomas C. Kingsley; Ramesh Raskar (CoRR, 2021)

Status-quo Policy Gradient in Multi-Agent Reinforcement Learning. - Pinkesh Badjatiya; Mausoom Sarkar; Nikaash Puri; Jayakumar Subramanian; Abhishek Sinha; Siddharth Singh; Balaji Krishnamurthy (AAMAS, 2022)

Differentiable Agent-based Epidemiology. - Ayush Chopra; Alexander Rodríguez; Jayakumar Subramanian; Balaji Krishnamurthy; B. Aditya Prakash; Ramesh Raskar (CoRR, 2022)

Approximate Information State for Approximate Planning and Reinforcement Learning in Partially Observed Systems. - Jayakumar Subramanian; Amit Sinha; Raihan Seraj; Aditya Mahajan (J. Mach. Learn. Res., 2022)

Differentiable Agent-based Epidemiology. - Ayush Chopra; Alexander Rodríguez; Jayakumar Subramanian; Arnau Quera-Bofarull; Balaji Krishnamurthy; B. Aditya Prakash; Ramesh Raskar (AAMAS, 2023)

Explaining RL Decisions with Trajectories. - Shripad Vilasrao Deshmukh; Arpan Dasgupta; Balaji Krishnamurthy; Nan Jiang; Chirag Agarwal; Georgios Theocharous; Jayakumar Subramanian (ICLR, 2023)

SARC: Soft Actor Retrospective Critic. - Sukriti Verma; Ayush Chopra; Jayakumar Subramanian; Mausoom Sarkar; Nikaash Puri; Piyush Gupta; Balaji Krishnamurthy (CoRR, 2023)

Counterfactual Explanation Policies in RL. - Shripad Vilasrao Deshmukh; Srivatsan R; Supriti Vijay; Jayakumar Subramanian; Chirag Agarwal (CoRR, 2023)

Mean-field games among teams. - Jayakumar Subramanian; Akshat Kumar; Aditya Mahajan (CoRR, 2023)

Behavior Optimized Image Generation. - Varun Khurana; Yaman Kumar Singla; Jayakumar Subramanian; Rajiv Ratn Shah; Changyou Chen; Zhiqiang Xu; Balaji Krishnamurthy (CoRR, 2023)

Robustness and Sample Complexity of Model-Based MARL for General-Sum Markov Games. - Jayakumar Subramanian; Amit Sinha; Aditya Mahajan (Dyn. Games Appl., 2023)

flame: A Framework for Learning in Agent-based ModEls. - Ayush Chopra; Jayakumar Subramanian; Balaji Krishnamurthy; Ramesh Raskar (AAMAS, 2024)

Measuring And Improving Engagement of Text-to-Image Generation Models. - Varun Khurana; Yaman Kumar Singla; Jayakumar Subramanian; Changyou Chen; Rajiv Ratn Shah; Zhiqiang Xu; Balaji Krishnamurthy (ICLR, 2025)

Learning to Clarify by Reinforcement Learning Through Reward-Weighted Fine-Tuning. - Subhojyoti Mukherjee; Viet Dac Lai; Raghavendra Addanki; Ryan A. Rossi; Seunghyun Yoon 002; Trung Bui; Anup B. Rao; Jayakumar Subramanian; Branislav Kveton (CoRR, 2025)

Lizard: An Efficient Linearization Framework for Large Language Models. - Chien Van Nguyen; Ruiyi Zhang 002; Hanieh Deilamsalehy; Puneet Mathur; Viet Dac Lai; Haoliang Wang; Jayakumar Subramanian; Ryan A. Rossi; Trung Bui; Nikos Vlassis; Franck Dernoncourt; Thien Huu Nguyen (CoRR, 2025)