Abhinav Verma

According to our database, Abhinav Verma authored at least 10 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Deep Policy Optimization with Temporal Logic Constraints.

Ameesh Shah, Cameron Voloshin, Chenxi Yang, Abhinav Verma, Swarat Chaudhuri, Sanjit A. Seshia

CoRR, 2024

2023

Eventual Discounting Temporal Logic Counterfactual Experience Replay.

Cameron Voloshin, Abhinav Verma, Yisong Yue

Proceedings of the International Conference on Machine Learning, 2023

2020

Learning Differentiable Programs with Admissible Neural Heuristics.

Ameesh Shah, Eric Zhan, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Neurosymbolic Reinforcement Learning with Formally Verified Exploration.

Greg Anderson, Abhinav Verma, Isil Dillig, Swarat Chaudhuri

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Imitation-Projected Policy Gradient for Programmatic Reinforcement Learning.

Abhinav Verma, Hoang Minh Le, Yisong Yue, Swarat Chaudhuri

CoRR, 2019

Imitation-Projected Programmatic Reinforcement Learning.

Abhinav Verma, Hoang Minh Le, Yisong Yue, Swarat Chaudhuri

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Control Regularization for Reduced Variance Reinforcement Learning.

Richard Cheng, Abhinav Verma, Gábor Orosz, Swarat Chaudhuri, Yisong Yue, Joel Burdick

Proceedings of the 36th International Conference on Machine Learning, 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

Proceedings of the 7th International Conference on Learning Representations, 2019

Verifiable and Interpretable Reinforcement Learning through Program Synthesis.

Abhinav Verma

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Programmatically Interpretable Reinforcement Learning.

Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri

Proceedings of the 35th International Conference on Machine Learning, 2018