Robustness to Adversarial Attacks in Learning-Enabled Controllers. - Zikang Xiong; Joe Eappen; He Zhu 001; Suresh Jagannathan (CoRR, 2020)

Model-free Neural Lyapunov Control for Safe Robot Navigation. - Zikang Xiong; Joe Eappen; Ahmed H. Qureshi; Suresh Jagannathan (IROS, 2022)

DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems. - Joe Eappen; Suresh Jagannathan (ECML/PKDD (4), 2022)

Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising. - Zikang Xiong; Joe Eappen; He Zhu 001; Suresh Jagannathan (ECML/PKDD (3), 2022)

Co-learning Planning and Control Policies Using Differentiable Formal Task Constraints. - Zikang Xiong; Joe Eappen; Daniel Lawson; Ahmed H. Qureshi; Suresh Jagannathan (CoRR, 2023)

Scaling Safe Multi-Agent Control for Signal Temporal Logic Specifications. - Joe Eappen; Zikang Xiong; Dipam Patel; Aniket Bera; Suresh Jagannathan (CoRL, 2024)

Information-Directed Pessimism for Offline Reinforcement Learning. - Alec Koppel; Sujay Bhatt; Jiacheng Guo; Joe Eappen; Mengdi Wang; Sumitra Ganesh (ICML, 2024)

Co-learning Planning and Control Policies Constrained by Differentiable Logic Specifications. - Zikang Xiong; Daniel Lawson; Joe Eappen; Ahmed H. Qureshi; Suresh Jagannathan (ICRA, 2024)

Online MCMC Thinning with Kernelized Stein Discrepancy. - Alec Koppel; Joe Eappen; Sujay Bhatt; Cole Hawkins; Sumitra Ganesh (SIAM J. Math. Data Sci., 2024)

A Framework for Learning Scoring Rules in Autonomous Driving Planning Systems. - Zikang Xiong; Joe Eappen; Suresh Jagannathan (CoRR, 2025)

FLoRA: A Framework for Learning Scoring Rules in Autonomous Driving Planning Systems. - Zikang Xiong; Joe Eappen; Suresh Jagannathan (IEEE Robotics Autom. Lett., 2025)