Khimya Khetarpal

According to our database, Khimya Khetarpal authored at least 33 papers between 2016 and 2025.

Collaborative distances:

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

2025

Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning.

Daniel Lawson, Adriana Hugessen, Charlotte Cloutier, Glen Berseth, Khimya Khetarpal

CoRR, June, 2025

Plasticity as the Mirror of Empowerment.

David Abel, Michael Bowling, André Barreto, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh

CoRR, May, 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

CoRR, April, 2025

Representation Learning via Non-Contrastive Mutual Information.

Zhaohan Daniel Guo, Bernardo Ávila Pires, Khimya Khetarpal, Dale Schuurmans, Bo Dai

CoRR, April, 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 S. Srinivasa

CoRR, April, 2025

Agency Is Frame-Dependent.

David Abel, André Barreto, Michael Bowling, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh

CoRR, February, 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

CoRR, January, 2025

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning.

Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L. Borsa, Arthur Guez, Will Dabney

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Toward Human-AI Alignment in Large-Scale Multi-Player Games.

Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad

CoRR, 2024

Balancing Context Length and Mixing Times for Reinforcement Learning at Scale.

Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Normalization and effective learning rates in reinforcement learning.

Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado Philip van Hasselt, Razvan Pascanu, Will Dabney

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Conference on Lifelong Learning Agents, 2024

2023

POMRL: No-Regret Learning-to-Plan with Increasing Horizons.

Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy

Trans. Mach. Learn. Res., 2023

Forecaster: Towards Temporally Abstract Tree-Search Planning from Pixels.

Thomas Jiralerspong, Flemming Kondrup, Doina Precup, Khimya Khetarpal

CoRR, 2023

Discovering Object-Centric Generalized Value Functions From Pixels.

Somjit Nath, Gopeshh Raaj Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou

Proceedings of the International Conference on Machine Learning, 2023

2022

Towards Continual Reinforcement Learning: A Review and Perspectives.

Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup

J. Artif. Intell. Res., 2022

The Paradox of Choice: Using Attention in Hierarchical Reinforcement Learning.

Andrei Cristian Nica, Khimya Khetarpal, Doina Precup

CoRR, 2022

2021

Safe option-critic: learning safety in the option-critic architecture.

Arushi Jain, Khimya Khetarpal, Doina Precup

Knowl. Eng. Rev., 2021

Sequoia: A Software Framework to Unify Continual Learning Research.

Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodríguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia

CoRR, 2021

Temporally Abstract Partial Models.

Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Robust State Abstractions for Hidden-Parameter Block MDPs.

Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau

Proceedings of the 9th International Conference on Learning Representations, 2021

Self-Supervised Attention-Aware Reinforcement Learning.

Haiping Wu, Khimya Khetarpal, Doina Precup

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Variance Penalized On-Policy and Off-Policy Actor-Critic.

Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP.

Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau

CoRR, 2020

What can I do here? A Theory of Affordances in Reinforcement Learning.

Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup

Proceedings of the 37th International Conference on Machine Learning, 2020

Value Preserving State-Action Abstractions.

David Abel, Nate Umbanhowar, Khimya Khetarpal, Dilip Arumugam, Doina Precup, Michael L. Littman

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Options of Interest: Temporal Abstraction with Interest Functions.

Khimya Khetarpal, Martin Klissarov, Maxime Chevalier-Boisvert, Pierre-Luc Bacon, Doina Precup

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning Options with Interest Functions.

Khimya Khetarpal, Doina Precup

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

Learning Generalized Temporal Abstractions across Both Action and Perception.

Khimya Khetarpal

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

2018

Environments for Lifelong Reinforcement Learning.

Khimya Khetarpal, Shagun Sodhani, Sarath Chandar, Doina Precup

CoRR, 2018

Attend Before you Act: Leveraging human visual attention for continual learning.

Khimya Khetarpal, Doina Precup

CoRR, 2018

2017

Creating Segments and Effects on Comics by Clustering Gaze Data.

Ishwarya Thirunarayanan, Khimya Khetarpal, Sanjeev J. Koppal, Olivier Le Meur, John M. Shea, Eakta Jain

ACM Trans. Multim. Comput. Commun. Appl., 2017

2016

A preliminary benchmark of four saliency algorithms on comic art.

Khimya Khetarpal, Eakta Jain

Proceedings of the 2016 IEEE International Conference on Multimedia & Expo Workshops, 2016