Anytime Integrated Task and Motion Policies for Stochastic Environments. - Naman Shah 002; Siddharth Srivastava 001 (CoRR, 2019)

Anytime Integrated Task and Motion Policies for Stochastic Environments. - Naman Shah 002; Deepak Kala Vasudevan; Kislay Kumar; Pranav Kamojjhala; Siddharth Srivastava 001 (ICRA, 2020)

Learning Sampling Distributions for Efficient High-Dimensional Motion Planning. - Naman Shah 002; Abhyudaya Srinet; Siddharth Srivastava 001 (CoRR, 2020)

Anytime Stochastic Task and Motion Policies. - Naman Shah 002; Siddharth Srivastava 001 (CoRR, 2021)

JEDAI Explains Decision-Making AI. - Trevor Angle; Naman Shah 002; Pulkit Verma 001; Siddharth Srivastava 001 (CoRR, 2021)

JEDAI: A System for Skill-Aligned Explainable Robot Planning. - Naman Shah 002; Pulkit Verma 001; Trevor Angle; Siddharth Srivastava 001 (AAMAS, 2022)

Using Deep Learning to Bootstrap Abstractions for Hierarchical Robot Planning. - Naman Shah 002; Siddharth Srivastava 001 (AAMAS, 2022)

Multi-Task Option Learning and Discovery for Stochastic Path Planning. - Naman Shah 002; Siddharth Srivastava 001 (CoRR, 2022)

Reliable Neuro-Symbolic Abstractions for Planning and Learning. - Naman Shah 002 (IJCAI, 2023)

Learning Neuro-Symbolic Abstractions for Robot Planning and Learning. - Naman Shah 002 (AAAI, 2024)

Hierarchical Planning and Learning for Robots in Stochastic Settings Using Zero-Shot Option Invention. - Naman Shah 002; Siddharth Srivastava 001 (AAAI, 2024)

From Reals to Logic and Back: Inventing Symbolic Vocabularies, Actions, and Models for Planning from Raw Data. - Naman Shah 002; Jayesh Nagpal; Pulkit Verma 001; Siddharth Srivastava 001 (CoRR, 2024)

Using Explainable AI and Hierarchical Planning for Outreach with Robots. - Rushang Karia; Jayesh Nagpal; Daksh Dobhal; Pulkit Verma 001; Rashmeet Kaur Nayyar; Naman Shah 002; Siddharth Srivastava 001 (AAAI, 2025)