Nishanth Kumar

According to our database, Nishanth Kumar authored at least 17 papers between 2019 and 2024.

Collaborative distances:

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

2024

Practice Makes Perfect: Planning to Learn Skill Parameter Policies.

Nishanth Kumar, Tom Silver, Willie McClinton, Linfeng Zhao, Stephen Proulx, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Jennifer L. Barry

CoRR, 2024

Preference-Conditioned Language-Guided Abstraction.

Andi Peng, Andreea Bobu, Belinda Z. Li, Theodore R. Sumers, Ilia Sucholutsky, Nishanth Kumar, Thomas L. Griffiths, Julie A. Shah

Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024

2023

Economic Trading Susceptibility: Constructing Networks of Mutual Influence through the Fitness of Countries.

Nishanth Kumar, Henrik Jeldtoft Jensen, Eduardo Viegas

Entropy, January, 2023

Learning Efficient Abstract Planning Models that Choose What to Predict.

Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver, Tomás Lozano-Pérez, Leslie Pack Kaelbling

Proceedings of the Conference on Robot Learning, 2023

Predicate Invention for Bilevel Planning.

Tom Silver, Rohan Chitnis, Nishanth Kumar, Willie McClinton, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning Operators with Ignore Effects for Bilevel Planning in Continuous Domains.

Nishanth Kumar, Willie McClinton, Rohan Chitnis, Tom Silver, Tomás Lozano-Pérez, Leslie Pack Kaelbling

CoRR, 2022

Inventing Relational State and Action Abstractions for Effective and Efficient Bilevel Planning.

Tom Silver, Rohan Chitnis, Nishanth Kumar, Willie McClinton, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum

CoRR, 2022

PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX.

Guangyao Zhou, Nishanth Kumar, Miguel Lázaro-Gredilla, Shrinu Kushagra, Dileep George

CoRR, 2022

2021

Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes.

Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun

CoRR, 2021

Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes.

Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Rate of change analysis for interestingness measures.

Nandan Sudarsanam, Nishanth Kumar, Abhishek Sharma, Balaraman Ravindran

Knowl. Inf. Syst., 2020

Task Scoping: Building Goal-Specific Abstractions for Planning in Complex Domains.

Nishanth Kumar, Michael Fishman, Natasha Danas, Michael Littman, Stefanie Tellex, George Konidaris

CoRR, 2020

The Past and Present of Imitation Learning: A Citation Chain Study.

Nishanth Kumar

CoRR, 2020

Building Plannable Representations with Mixed Reality.

Eric Rosen, Nishanth Kumar, Nakul Gopalan, Daniel Ullman, George Konidaris, Stefanie Tellex

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Task Scoping for Efficient Planning in Open Worlds (Student Abstract).

Nishanth Kumar, Michael Fishman, Natasha Danas, Stefanie Tellex, Michael Littman, George Konidaris

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

2019

Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control.

Jonathan Chang, Nishanth Kumar, Sean Hastings, Aaron Gokaslan, Diego Romeres, Devesh K. Jha, Daniel Nikovski, George Dimitri Konidaris, Stefanie Tellex

CoRR, 2019

Multi-Object Search using Object-Oriented POMDPs.

Arthur Wandzel, Yoonseon Oh, Michael Fishman, Nishanth Kumar, Lawson L. S. Wong, Stefanie Tellex

Proceedings of the International Conference on Robotics and Automation, 2019