Scalable Inference for Logistic-Normal Topic Models. - Jianfei Chen 001; Jun Zhu 001; Zi Wang; Xun Zheng; Bo Zhang 010 (NIPS, 2013)

Dropout Training for Support Vector Machines. - Ning Chen 002; Jun Zhu 001; Jianfei Chen 001; Bo Zhang 010 (AAAI, 2014)

Bayesian Max-margin Multi-Task Learning with Data Augmentation. - Chengtao Li; Jun Zhu 001; Jianfei Chen 001 (ICML, 2014)

TopicPanorama: A full picture of relevant topics. - Shixia Liu; Xiting Wang; Jianfei Chen 001; Jim Zhu; Baining Guo (IEEE VAST, 2014)

Big Learning with Bayesian Methods. - Jun Zhu 001; Jianfei Chen 001; Wenbo Hu 001 (CoRR, 2014)

WarpLDA: a Simple and Efficient O(1) Algorithm for Latent Dirichlet Allocation. - Jianfei Chen 001; Kaiwei Li; Jun Zhu 001; Wenguang Chen (CoRR, 2015)

Distributing the Stochastic Gradient Sampler for Large-Scale LDA. - Yuan Yang; Jianfei Chen 001; Jun Zhu 001 (KDD, 2016)

Scaling up Dynamic Topic Models. - Arnab Bhadury; Jianfei Chen 001; Jun Zhu 001; Shixia Liu (WWW, 2016)

Streaming Gibbs Sampling for LDA Model. - Yang Gao; Jianfei Chen 001; Jun Zhu 001 (CoRR, 2016)

WarpLDA: a Cache Efficient O(1) Algorithm for Latent Dirichlet Allocation. - Jianfei Chen 001; Kaiwei Li; Jun Zhu 001; Wenguang Chen (Proc. VLDB Endow., 2016)

TopicPanorama: A Full Picture of Relevant Topics. - Xiting Wang; Shixia Liu; Junlin Liu; Jianfei Chen 001; Jun Zhu 001; Baining Guo (IEEE Trans. Vis. Comput. Graph., 2016)

Population Matching Discrepancy and Applications in Deep Learning. - Jianfei Chen 001; Chongxuan Li; Yizhong Ru; Jun Zhu 001 (NIPS, 2017)

Scalable Inference for Nested Chinese Restaurant Process Topic Models. - Jianfei Chen 001; Jun Zhu 001; Jie Lu; Shixia Liu (CoRR, 2017)

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)

Stochastic Training of Graph Convolutional Networks. - Jianfei Chen 001; Jun Zhu 001 (CoRR, 2017)

Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems. - Zihao Xiao 002; Jianfei Chen 001; Jun Zhu 001 (AAAI, 2018)

Stochastic Training of Graph Convolutional Networks with Variance Reduction. - Jianfei Chen 001; Jun Zhu 001; Le Song (ICML, 2018)

Stochastic Expectation Maximization with Variance Reduction. - Jianfei Chen 001; Jun Zhu 001; Yee Whye Teh; Tong Zhang 001 (NeurIPS, 2018)

Dropout training for SVMs with data augmentation. - Ning Chen 002; Jun Zhu 001; Jianfei Chen 001; Ting Chen 006 (Frontiers Comput. Sci., 2018)

Scalable Training of Hierarchical Topic Models. - Jianfei Chen 001; Jun Zhu 001; Jie Lu; Shixia Liu (Proc. VLDB Endow., 2018)

VFlow: More Expressive Generative Flows with Variational Data Augmentation. - Jianfei Chen 001; Cheng Lu 011; Biqi Chenli; Jun Zhu 001; Tian Tian 001 (ICML, 2020)

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. - Kaiwei Li; Jianfei Chen 001; Wenguang Chen; Jun Zhu 001 (IEEE Trans. Parallel Distributed Syst., 2020)

Implicit Normalizing Flows. - Cheng Lu 011; Jianfei Chen 001; Chongxuan Li; Qiuhao Wang; Jun Zhu 001 (ICLR, 2021)

Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching. - Cheng Lu 011; Kaiwen Zheng; Fan Bao; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001 (ICML, 2022)

Fast Lossless Neural Compression with Integer-Only Discrete Flows. - Siyu Wang; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001; Bo Zhang 010 (ICML, 2022)

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. - Cheng Lu 011; Yuhao Zhou; Fan Bao; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001 (NeurIPS, 2022)

Deep Ensemble as a Gaussian Process Approximate Posterior. - Zhijie Deng; Feng Zhou 011; Jianfei Chen 001; Guoqiang Wu; Jun Zhu 001 (CoRR, 2022)

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. - Cheng Lu 011; Huayu Chen; Jianfei Chen 001; Hang Su 006; Chongxuan Li; Jun Zhu 001 (ICML, 2023)

Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs. - Kaiwen Zheng; Cheng Lu 011; Jianfei Chen 001; Jun Zhu 001 (ICML, 2023)

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics. - Kaiwen Zheng; Cheng Lu 011; Jianfei Chen 001; Jun Zhu 001 (NeurIPS, 2023)

Memory Efficient Optimizers with 4-bit States. - Bingrui Li; Jianfei Chen 001; Jun Zhu 001 (CoRR, 2023)

Investigating Uncertainty Calibration of Aligned Language Models under the Multiple-Choice Setting. - Guande He; Peng Cui 007; Jianfei Chen 001; Wenbo Hu 001; Jun Zhu 001 (CoRR, 2023)

Consistency Diffusion Bridge Models. - Guande He; Kaiwen Zheng; Jianfei Chen 001; Fan Bao; Jun Zhu 001 (NeurIPS, 2024)

C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory. - Tianjiao Luo; Tim Pearce; Huayu Chen; Jianfei Chen 001; Jun Zhu 001 (CoRR, 2024)

Calibrating Deep Ensemble through Functional Variational Inference. - Zhijie Deng; Feng Zhou 011; Jianfei Chen 001; Guoqiang Wu; Jun Zhu 001 (Trans. Mach. Learn. Res., 2024)

Elucidating the Preconditioning in Consistency Distillation. - Kaiwen Zheng; Guande He; Jianfei Chen 001; Fan Bao; Jun Zhu 001 (ICLR, 2025)

Diffusion Bridge Implicit Models. - Kaiwen Zheng; Guande He; Jianfei Chen 001; Fan Bao; Jun Zhu 001 (ICLR, 2025)

Visual Generation Without Guidance. - Huayu Chen; Kai Jiang; Kaiwen Zheng; Jianfei Chen 001; Hang Su 006; Jun Zhu 001 (CoRR, 2025)

SageAttention2++: A More Efficient Implementation of SageAttention2. - Jintao Zhang; Xiaoming Xu; Jia Wei; Haofeng Huang; Pengle Zhang; Chendong Xiang; Jun Zhu 001; Jianfei Chen 001 (CoRR, 2025)

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. - Cheng Lu 011; Yuhao Zhou; Fan Bao; Jianfei Chen 001; Chongxuan Li; Jun Zhu 001 (Mach. Intell. Res., 2025)