Abhinav Verma

According to our database, Abhinav Verma authored at least 19 papers between 2018 and 2026.

Collaborative distances:

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

2026

Scaling Strategy, Not Compute: A Stand-Alone, Open-Source StarCraft II Benchmark for Accessible Reinforcement Learning Research.

Sourav Panda, Shreyash Kale, Tanmay Ambadkar, Abhinav Verma, Jonathan Dodge

CoRR, March, 2026

Preference Conditioned Multi-Objective Reinforcement Learning: Decomposed, Diversity-Driven Policy Optimization.

Tanmay Ambadkar, Sourav Panda, Shreyash Kale, Jonathan Dodge, Abhinav Verma

CoRR, February, 2026

Safer Policies via Affine Representations Using Koopman Dynamics.

Tanmay Ambadkar, Darshan Chudiwal, Greg Anderson, Abhinav Verma

Proceedings of the NASA Formal Methods, 2026

Robust Adaptive Multi-Step Predictive Shielding (Student Abstract).

Tanmay Ambadkar, Darshan Chudiwal, Greg Anderson, Abhinav Verma

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Automating the Refinement of Reinforcement Learning Specifications.

Tanmay Ambadkar, Dorde Zikelic, Abhinav Verma

CoRR, December, 2025

NeuralStoc: A Tool for Neural Stochastic Control and Verification.

Matin Ansaripour, Krishnendu Chatterjee, Thomas A. Henzinger, Mathias Lechner, Abhinav Verma, Dorde Zikelic

Dataset, April, 2025

NeuralStoc: A Tool for Neural Stochastic Control and Verification.

Matin Ansaripour, Krishnendu Chatterjee, Thomas A. Henzinger, Mathias Lechner, Abhinav Verma, Dorde Zikelic

Dataset, April, 2025

LTL-Constrained Policy Optimization with Cycle Experience Replay.

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

Trans. Mach. Learn. Res., 2025

2024

Deep Policy Optimization with Temporal Logic Constraints.

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

CoRR, 2024

2023

Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.

Dorde Zikelic, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas A. Henzinger

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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