Khetarpal, Khimya

24 publications

AISTATS 2025 A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney
ICLRW 2025 Cracking the Code of Action: A Generative Approach to Affordances for Reinforcement Learning Lynn Cherif, Flemming Kondrup, David Venuto, Ankit Anand, Doina Precup, Khimya Khetarpal
CoRL 2025 Long Range Navigator (LRN): Extending Robot Planning Horizons Beyond Metric Maps Matt Schmittle, Rohan Baijal, Nathan Hatch, Rosario Scalise, Mateo Guaman Castro, Sidharth Talia, Khimya Khetarpal, Byron Boots, Siddhartha Srinivasa
JMLR 2025 Optimizing Return Distributions with Distributional Dynamic Programming Bernardo Ávila Pires, Mark Rowland, Diana Borsa, Zhaohan Daniel Guo, Khimya Khetarpal, André Barreto, David Abel, Rémi Munos, Will Dabney
NeurIPS 2025 Plasticity as the Mirror of Empowerment David Abel, Michael Bowling, Andre Barreto, Will Dabney, Shi Dong, Steven Stenberg Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh
NeurIPSW 2024 A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney
NeurIPS 2024 Balancing Context Length and Mixing Times for Reinforcement Learning at Scale Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar
CoLLAs 2024 Disentangling the Causes of Plasticity Loss in Neural Networks Clare Lyle, Zeyu Zheng, Khimya Khetarpal, Hado van Hasselt, Razvan Pascanu, James Martens, Will Dabney
NeurIPS 2024 Normalization and Effective Learning Rates in Reinforcement Learning Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado van Hasselt, Razvan Pascanu, Will Dabney
ICML 2023 Discovering Object-Centric Generalized Value Functions from Pixels Somjit Nath, Gopeshh Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou
NeurIPSW 2023 Forecaster: Towards Temporally Abstract Tree-Search Planning from Pixels Thomas Jiralerspong, Flemming Kondrup, Doina Precup, Khimya Khetarpal
TMLR 2023 POMRL: No-Regret Learning-to-Plan with Increasing Horizons Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy
NeurIPSW 2023 POMRL: No-Regret Learning-to-Plan with Increasing Horizons Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy
NeurIPSW 2022 The Paradox of Choice: On the Role of Attention in Hierarchical Reinforcement Learning Andrei Cristian Nica, Khimya Khetarpal, Doina Precup
JAIR 2022 Towards Continual Reinforcement Learning: A Review and Perspectives Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
ICLR 2021 Learning Robust State Abstractions for Hidden-Parameter Block MDPs Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau
AAAI 2021 Self-Supervised Attention-Aware Reinforcement Learning Haiping Wu, Khimya Khetarpal, Doina Precup
NeurIPS 2021 Temporally Abstract Partial Models Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup
AAAI 2021 Variance Penalized On-Policy and Off-Policy Actor-Critic Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup
AAAI 2020 Options of Interest: Temporal Abstraction with Interest Functions Khimya Khetarpal, Martin Klissarov, Maxime Chevalier-Boisvert, Pierre-Luc Bacon, Doina Precup
AISTATS 2020 Value Preserving State-Action Abstractions David Abel, Nate Umbanhowar, Khimya Khetarpal, Dilip Arumugam, Doina Precup, Michael Littman
ICML 2020 What Can I Do Here? a Theory of Affordances in Reinforcement Learning Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup
AAAI 2019 Learning Generalized Temporal Abstractions Across Both Action and Perception Khimya Khetarpal
AAAI 2019 Learning Options with Interest Functions Khimya Khetarpal, Doina Precup