Approximate Inference in Collective Graphical Models. - Daniel Sheldon; Tao Sun 008; Akshat Kumar; Thomas G. Dietterich (ICML (3), 2013)

Message Passing for Collective Graphical Models. - Tao Sun 008; Daniel Sheldon; Akshat Kumar (ICML, 2015)

A Probabilistic Approach for Learning with Label Proportions Applied to the US Presidential Election. - Tao Sun 008; Daniel Sheldon; Brendan O'Connor 001 (ICDM, 2017)

Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models. - Garrett Bernstein; Ryan McKenna; Tao Sun 008; Daniel Sheldon; Michael Hay; Gerome Miklau (ICML, 2017)

Three-quarter Sibling Regression for Denoising Observational Data. - Shiv Shankar; Daniel Sheldon; Tao Sun 008; John Pickering; Thomas G. Dietterich (IJCAI, 2019)

DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning. - Bharathan Balaji; Sunil Mallya; Sahika Genc; Saurabh Gupta; Leo Dirac; Vineet Khare; Gourav Roy; Tao Sun 008; Yunzhe Tao; Brian Townsend; Eddie Calleja; Sunil Muralidhara; et al. (CoRR, 2019)

DeepRacer: Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning. - Bharathan Balaji; Sunil Mallya; Sahika Genc; Saurabh Gupta; Leo Dirac; Vineet Khare; Gourav Roy; Tao Sun 008; Yunzhe Tao; Brian Townsend; Eddie Calleja; Sunil Muralidhara; et al. (ICRA, 2020)

Robust Multi-Agent Reinforcement Learning with Model Uncertainty. - Kaiqing Zhang; Tao Sun 008; Yunzhe Tao; Sahika Genc; Sunil Mallya; Tamer Basar (NeurIPS, 2020)

Zero-Shot Reinforcement Learning with Deep Attention Convolutional Neural Networks. - Sahika Genc; Sunil Mallya; Sravan Bodapati; Tao Sun 008; Yunzhe Tao (CoRR, 2020)

Gated Transformer for Decoding Human Brain EEG Signals. - Yunzhe Tao; Tao Sun 008; Aashiq Muhamed; Sahika Genc; Dylan Jackson; Ali Arsanjani; Suri Yaddanapudi; Liang Li; Prachi Kumar (EMBC, 2021)

REPAINT: Knowledge Transfer in Deep Reinforcement Learning. - Yunzhe Tao; Sahika Genc; Jonathan Chung 001; Tao Sun 008; Sunil Mallya (ICML, 2021)

B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis. - Zishun Yu; Yunzhe Tao; Liyu Chen; Tao Sun 008; Hongxia Yang (CoRR, 2023)