Verma, Abhinav

11 publications

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

IJCAI 2025 RetroMoE: A Mixture-of-Experts Latent Translation Framework for Single-Step Retrosynthesis Xinjie Li, Abhinav Verma

NeurIPS 2023 Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees Đorđe Žikelić, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas Henzinger

ICML 2023 Eventual Discounting Temporal Logic Counterfactual Experience Replay Cameron Voloshin, Abhinav Verma, Yisong Yue

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

NeurIPS 2020 Neurosymbolic Reinforcement Learning with Formally Verified Exploration Greg Anderson, Abhinav Verma, Isil Dillig, Swarat Chaudhuri

ICML 2019 Control Regularization for Reduced Variance Reinforcement Learning Richard Cheng, Abhinav Verma, Gabor Orosz, Swarat Chaudhuri, Yisong Yue, Joel Burdick

NeurIPS 2019 Imitation-Projected Programmatic Reinforcement Learning Abhinav Verma, Hoang Le, 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

AAAI 2019 Verifiable and Interpretable Reinforcement Learning Through Program Synthesis Abhinav Verma

ICML 2018 Programmatically Interpretable Reinforcement Learning Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri