Reduced variance deep reinforcement learning with temporal logic specifications. - Qitong Gao; Davood Hajinezhad; Yan Zhang 043; Yiannis Kantaros; Michael M. Zavlanos (ICCPS, 2019)

Model-Based Design of Closed Loop Deep Brain Stimulation Controller using Reinforcement Learning. - Qitong Gao; Michael Naumann; Ilija Jovanov; Vuk Lesi; Karthik Kumaravelu; Warren M. Grill 001; Miroslav Pajic (ICCPS, 2020)

Deep Imitative Reinforcement Learning for Temporal Logic Robot Motion Planning with Noisy Semantic Observations. - Qitong Gao; Miroslav Pajic; Michael M. Zavlanos (ICRA, 2020)

Deep Learning for Stable Monotone Dynamical Systems. - Yu Wang 044; Qitong Gao; Miroslav Pajic (CoRR, 2020)

Imputation-Free Learning from Incomplete Observations. - Qitong Gao; Dong Wang 037; Joshua D. Amason; Siyang Yuan; Chenyang Tao; Ricardo Henao; Majda Hadziahmetovic; Lawrence Carin; Miroslav Pajic (CoRR, 2021)

Learning Monotone Dynamics by Neural Networks. - Yu Wang 044; Qitong Gao; Miroslav Pajic (ACC, 2022)

Offline Policy Evaluation for Learning-based Deep Brain Stimulation Controllers. - Qitong Gao; Stephen L. Schmidt; Karthik Kamaravelu; Dennis A. Turner; Warren M. Grill 001; Miroslav Pajic (ICCPS, 2022)

Learning-Based Vulnerability Analysis of Cyber-Physical Systems. - Amir Khazraei; Spencer Hallyburton; Qitong Gao; Yu Wang 044; Miroslav Pajic (ICCPS, 2022)

Gradient Importance Learning for Incomplete Observations. - Qitong Gao; Dong Wang 037; Joshua David Amason; Siyang Yuan; Chenyang Tao; Ricardo Henao; Majda Hadziahmetovic; Lawrence Carin; Miroslav Pajic (ICLR, 2022)

A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification. - Ge Gao; Qitong Gao; Xi Yang 019; Miroslav Pajic; Min Chi (IJCAI, 2022)

Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment. - Qitong Gao; Stephen L. Schmidt; Afsana Chowdhury; Guangyu Feng; Jennifer J. Peters; Katherine Genty; Warren M. Grill 001; Dennis A. Turner; Miroslav Pajic (ICCPS, 2023)

Variational Latent Branching Model for Off-Policy Evaluation. - Qitong Gao; Ge Gao; Min Chi; Miroslav Pajic (ICLR, 2023)

Off-Policy Evaluation for Human Feedback. - Qitong Gao; Ge Gao; Juncheng Dong; Vahid Tarokh; Min Chi; Miroslav Pajic (NeurIPS, 2023)

Robust Reinforcement Learning through Efficient Adversarial Herding. - Juncheng Dong; Hao-Lun Hsu; Qitong Gao; Vahid Tarokh; Miroslav Pajic (CoRR, 2023)

ϵ-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment. - Hao-Lun Hsu; Qitong Gao; Miroslav Pajic (ICCPS, 2024)

On Trajectory Augmentations for Off-Policy Evaluation. - Ge Gao; Qitong Gao; Xi Yang 019; Song Ju; Miroslav Pajic; Min Chi (ICLR, 2024)

Steering Decision Transformers via Temporal Difference Learning. - Hao-Lun Hsu; Alper Kamil Bozkurt; Juncheng Dong; Qitong Gao; Vahid Tarokh; Miroslav Pajic (IROS, 2024)

Off-Policy Selection for Initiating Human-Centric Experimental Design. - Ge Gao; Xi Yang 019; Qitong Gao; Song Ju; Miroslav Pajic; Min Chi (NeurIPS, 2024)

Variational Adversarial Training Towards Policies with Improved Robustness. - Juncheng Dong; Hao-Lun Hsu; Qitong Gao; Vahid Tarokh; Miroslav Pajic (AISTATS, 2025)