Han, Jun

11 publications

TMLR 2025 Guided Discrete Diffusion for Electronic Health Record Generation Jun Han, Zixiang Chen, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu

ICLR 2022 Generative Principal Component Analysis Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett

IJCAI 2022 Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors Zhaoqiang Liu, Jun Han

ICLR 2021 Disentangled Recurrent Wasserstein Autoencoder Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang

AISTATS 2020 Stein Variational Inference for Discrete Distributions Jun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu

AAAI 2019 Biomedical Image Segmentation via Representative Annotation Hao Zheng, Lin Yang, Jianxu Chen, Jun Han, Yizhe Zhang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen

NeurIPS 2019 Deep Generative Video Compression Salvator Lombardo, Jun Han, Christopher Schroers, Stephan Mandt

ICML 2018 Stein Variational Gradient Descent Without Gradient Jun Han, Qiang Liu

UAI 2017 Stein Variational Adaptive Importance Sampling Jun Han, Qiang Liu

NeurIPS 2016 Bootstrap Model Aggregation for Distributed Statistical Learning Jun Han, Qiang Liu

IJCAI 2013 Crowdsourcing-Assisted Query Structure Interpretation Jun Han, Ju Fan, Lizhu Zhou