Jianfei Chen

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 36

Top Topics

Chinese Restaurant Process

Top Venues

Proc. VLDB Endow.

Publications

Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory. CoRR (2024)
Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs. ICML (2023)
Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs. CoRR (2023)
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. ICML (2023)
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu
Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. CoRR (2023)
Bingrui Li, Jianfei Chen, Jun Zhu
Memory Efficient Optimizers with 4-bit States. CoRR (2023)
Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching. ICML (2022)
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. CoRR (2022)
Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu
Deep Ensemble as a Gaussian Process Approximate Posterior. CoRR (2022)
Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
Fast Lossless Neural Compression with Integer-Only Discrete Flows. ICML (2022)
Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
Fast Lossless Neural Compression with Integer-Only Discrete Flows. CoRR (2022)
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. CoRR (2022)
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. NeurIPS (2022)
Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching. CoRR (2022)
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
Implicit Normalizing Flows. ICLR (2021)
Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
Implicit Normalizing Flows. CoRR (2021)
Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian
VFlow: More Expressive Generative Flows with Variational Data Augmentation. CoRR (2020)
Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. IEEE Trans. Parallel Distributed Syst. 31 (9) (2020)
Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian
VFlow: More Expressive Generative Flows with Variational Data Augmentation. ICML (2020)
Zihao Xiao, Jianfei Chen, Jun Zhu
Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems. AAAI (2018)
Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu
Scalable Training of Hierarchical Topic Models. Proc. VLDB Endow. 11 (7) (2018)
Jianfei Chen, Jun Zhu, Le Song
Stochastic Training of Graph Convolutional Networks with Variance Reduction. ICML (2018)
Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen
Dropout training for SVMs with data augmentation. Frontiers Comput. Sci. 12 (4) (2018)
Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang
Stochastic Expectation Maximization with Variance Reduction. NeurIPS (2018)
Zihao Xiao, Jianfei Chen, Jun Zhu
Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems. CoRR (2018)
Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. ASPLOS (2017)
Jiaxin Shi, Jianfei Chen, Jun Zhu, Shengyang Sun, Yucen Luo, Yihong Gu, Yuhao Zhou
ZhuSuan: A Library for Bayesian Deep Learning. CoRR (2017)
Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu
Scalable Inference for Nested Chinese Restaurant Process Topic Models. CoRR (2017)
Jianfei Chen, Jun Zhu
Stochastic Training of Graph Convolutional Networks. CoRR (2017)
Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu
Population Matching Discrepancy and Applications in Deep Learning. NIPS (2017)
Xiting Wang, Shixia Liu, Junlin Liu, Jianfei Chen, Jun Zhu, Baining Guo
TopicPanorama: A Full Picture of Relevant Topics. IEEE Trans. Vis. Comput. Graph. 22 (12) (2016)
Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. CoRR (2016)
Yang Gao, Jianfei Chen, Jun Zhu
Streaming Gibbs Sampling for LDA Model. CoRR (2016)
Arnab Bhadury, Jianfei Chen, Jun Zhu, Shixia Liu
Scaling up Dynamic Topic Models. WWW (2016)
Yuan Yang, Jianfei Chen, Jun Zhu
Distributing the Stochastic Gradient Sampler for Large-Scale LDA. KDD (2016)
Jianfei Chen, Kaiwei Li, Jun Zhu, Wenguang Chen
WarpLDA: a Cache Efficient O(1) Algorithm for Latent Dirichlet Allocation. Proc. VLDB Endow. 9 (10) (2016)
Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen
Dropout Training for SVMs with Data Augmentation. CoRR (2015)
Jianfei Chen, Kaiwei Li, Jun Zhu, Wenguang Chen
WarpLDA: a Simple and Efficient O(1) Algorithm for Latent Dirichlet Allocation. CoRR (2015)
Shixia Liu, Xiting Wang, Jianfei Chen, Jim Zhu, Baining Guo
TopicPanorama: A full picture of relevant topics. IEEE VAST (2014)
Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang
Dropout Training for Support Vector Machines. AAAI (2014)
Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang
Dropout Training for Support Vector Machines. CoRR (2014)
Chengtao Li, Jun Zhu, Jianfei Chen
Bayesian Max-margin Multi-Task Learning with Data Augmentation. ICML (2014)
Jun Zhu, Jianfei Chen, Wenbo Hu
Big Learning with Bayesian Methods. CoRR (2014)
Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang
Scalable Inference for Logistic-Normal Topic Models. NIPS (2013)