On the relationship between multitask neural networks and multitask Gaussian Processes. - Karthikeyan K; Shubham Kumar Bharti; Piyush Rai (CoRR, 2019)

The Teaching Dimension of Q-learning. - Xuezhou Zhang; Shubham Kumar Bharti; Yuzhe Ma; Adish Singla; Xiaojin Zhu 001 (CoRR, 2020)

The Sample Complexity of Teaching by Reinforcement on Q-Learning. - Xuezhou Zhang; Shubham Kumar Bharti; Yuzhe Ma; Adish Singla; Xiaojin Zhu 001 (AAAI, 2021)

Provable Defense against Backdoor Policies in Reinforcement Learning. - Shubham Kumar Bharti; Xuezhou Zhang; Adish Singla; Jerry Zhu (NeurIPS, 2022)

Provable Defense against Backdoor Policies in Reinforcement Learning. - Shubham Kumar Bharti; Xuezhou Zhang; Adish Singla; Xiaojin Zhu 001 (CoRR, 2022)

Optimally Teaching a Linear Behavior Cloning Agent. - Shubham Kumar Bharti; Stephen Wright; Adish Singla; Xiaojin Zhu 001 (CoRR, 2023)

On the Complexity of Teaching a Family of Linear Behavior Cloning Learners. - Shubham Kumar Bharti; Stephen Wright; Adish Singla; Xiaojin (Jerry) Zhu (NeurIPS, 2024)

CHARTOM: A Visual Theory-of-Mind Benchmark for Multimodal Large Language Models. - Shubham Kumar Bharti; Shiyun Cheng; Jihyun Rho; Martina Rao; Xiaojin Zhu 001 (CoRR, 2024)

In-Context Learning with Hypothesis-Class Guidance. - Ziqian Lin; Shubham Kumar Bharti; Kangwook Lee 001 (CoRR, 2025)