Shah, Ameesh

6 publications

TMLR 2025 LTL-Constrained Policy Optimization with Cycle Experience Replay Ameesh Shah, Cameron Voloshin, Chenxi Yang, Abhinav Verma, Swarat Chaudhuri, Sanjit A. Seshia

NeurIPS 2025 Robust and Diverse Multi-Agent Learning via Rational Policy Gradient Niklas Lauffer, Ameesh Shah, Micah Carroll, Sanjit A. Seshia, Stuart Russell, Michael D Dennis

ICMLW 2023 Learning Formal Specifications from Membership and Preference Queries Ameesh Shah, Marcell Vazquez-Chanlatte, Sebastian Junges, Sanjit A. Seshia

ICML 2023 Who Needs to Know? Minimal Knowledge for Optimal Coordination Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael D Dennis, Stuart Russell

NeurIPS 2020 Learning Differentiable Programs with Admissible Neural Heuristics Ameesh Shah, Eric Zhan, Jennifer Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri

ICLR 2019 Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel