Conditional Generative Moment-Matching Networks. - Yong Ren; Jun Zhu 001; Jialian Li; Yucen Luo (NIPS, 2016)

ZhuSuan: A Library for Bayesian Deep Learning. - Jiaxin Shi; Jianfei Chen 001; Jun Zhu 001; Shengyang Sun; Yucen Luo; Yihong Gu; Yuhao Zhou (CoRR, 2017)

Smooth Neighbors on Teacher Graphs for Semi-Supervised Learning. - Yucen Luo; Jun Zhu 001; Mengxi Li; Yong Ren; Bo Zhang 010 (CVPR, 2018)

Semi-crowdsourced Clustering with Deep Generative Models. - Yucen Luo; Tian Tian 001; Jiaxin Shi; Jun Zhu 001; Bo Zhang 010 (NeurIPS, 2018)

Cluster Alignment With a Teacher for Unsupervised Domain Adaptation. - Zhijie Deng; Yucen Luo; Jun Zhu 001 (ICCV, 2019)

A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels. - Yucen Luo; Jun Zhu 001; Tomas Pfister (CoRR, 2019)

DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures. - Zhijie Deng; Yucen Luo; Jun Zhu 001; Bo Zhang 010 (CoRR, 2019)

SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models. - Yucen Luo; Alex Beatson; Mohammad Norouzi 002; Jun Zhu 001; David Duvenaud; Ryan P. Adams; Ricky T. Q. Chen (ICLR, 2020)

Improving Generative Moment Matching Networks with Distribution Partition. - Yong Ren; Yucen Luo; Jun Zhu 001 (AAAI, 2021)

Spectral Representation Learning for Conditional Moment Models. - Ziyu Wang 006; Yucen Luo; Yueru Li; Jun Zhu 001; Bernhard Schölkopf (CoRR, 2022)

Iterative Teaching by Data Hallucination. - Zeju Qiu; Weiyang Liu; Tim Z. Xiao; Zhen Liu 019; Umang Bhatt; Yucen Luo; Adrian Weller; Bernhard Schölkopf (AISTATS, 2023)

Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation. - Zhijie Deng; Yucen Luo (ICCV, 2023)

Learning Counterfactually Invariant Predictors. - Francesco Quinzan; Cecilia Casolo; Krikamol Muandet; Yucen Luo; Niki Kilbertus (Trans. Mach. Learn. Res., 2024)