Modeling and Predicting the Outcomes of NBA Basketball Games. - Yasi Zhang; Sicheng Zhou; Xi Zheng; Yuyu Wang; Minrui Liang (ESSE, 2021)

Transductive Matrix Completion with Calibration for Multi-Task Learning. - Hengfang Wang; Yasi Zhang; Xiaojun Mao; Zhonglei Wang (ICASSP, 2023)

Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation. - Yingshan Chang; Yasi Zhang; Zhiyuan Fang; Ying Nian Wu; Yonatan Bisk; Feng Gao 013 (ECCV (87), 2024)

Object-Conditioned Energy-Based Attention Map Alignment in Text-to-Image Diffusion Models. - Yasi Zhang; Peiyu Yu; Ying Nian Wu (ECCV (42), 2024)

Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching. - Yasi Zhang; Peiyu Yu; Yaxuan Zhu; Yingshan Chang; Feng Gao 013; Ying Nian Wu; Oscar Leong (NeurIPS, 2024)

Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. - Peiyu Yu; Dinghuai Zhang; Hengzhi He; Xiaojian Ma 001; Ruiyao Miao; Yifan Lu; Yasi Zhang; Deqian Kong; Ruiqi Gao; Jianwen Xie; Guang Cheng 003; Ying Nian Wu (CoRR, 2024)

Think Twice Before You Act: Improving Inverse Problem Solving With MCMC. - Yaxuan Zhu; Zehao Dou; Haoxin Zheng; Yasi Zhang; Ying Nian Wu; Ruiqi Gao (CoRR, 2024)

DODT: Enhanced Online Decision Transformer Learning through Dreamer's Actor-Critic Trajectory Forecasting. - Eric Hanchen Jiang; Zhi Zhang 012; Dinghuai Zhang; Andrew Lizarraga; Chenheng Xu; Yasi Zhang; Siyan Zhao; Zhengjie Xu; Peiyu Yu; Yuer Tang; Deqian Kong; Ying Nian Wu (CoRR, 2024)

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory. - Zhi Zhang 012; Chris Chow; Yasi Zhang; Yanchao Sun; Haochen Zhang; Eric Hanchen Jiang; Han Liu 001; Furong Huang; Yuchen Cui; Oscar Hernan Madrid Padilla (CoRR, 2024)

Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory. - Eric Hanchen Jiang; Yasi Zhang; Zhi Zhang 012; Yixin Wan; Andrew Lizarraga; Shufan Li; Ying Nian Wu (CoRR, 2024)

Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory. - Zhi Zhang 012; Chris Chow; Yasi Zhang; Yanchao Sun; Haochen Zhang; Eric Hanchen Jiang; Han Liu 001; Furong Huang; Yuchen Cui; Oscar Hernan Madrid Padilla (AISTATS, 2025)

Learning Difference-of-Convex Regularizers for Inverse Problems: A Flexible Framework with Theoretical Guarantees. - Yasi Zhang; Oscar Leong (CoRR, 2025)

Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation. - Tianyu Chen; Yasi Zhang; Zhendong Wang; Ying Nian Wu; Oscar Leong; Mingyuan Zhou (CoRR, 2025)

Restoration Score Distillation: From Corrupted Diffusion Pretraining to One-Step High-Quality Generation. - Yasi Zhang; Tianyu Chen; Zhendong Wang; Ying Nian Wu; Mingyuan Zhou; Oscar Leong (CoRR, 2025)