Jianfei Chen

According to our database, Jianfei Chen authored at least 33 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory.

Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu

CoRR, 2024

2023

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics.

Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

CoRR, 2023

Memory Efficient Optimizers with 4-bit States.

Bingrui Li, Jianfei Chen, Jun Zhu

CoRR, 2023

Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs.

Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

Proceedings of the International Conference on Machine Learning, 2023

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning.

Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu

Proceedings of the International Conference on Machine Learning, 2023

2022

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

CoRR, 2022

Deep Ensemble as a Gaussian Process Approximate Posterior.

Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu

CoRR, 2022

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.

Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fast Lossless Neural Compression with Integer-Only Discrete Flows.

Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang

Proceedings of the International Conference on Machine Learning, 2022

Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching.

Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

Proceedings of the International Conference on Machine Learning, 2022

2021

Implicit Normalizing Flows.

Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs.

Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu

IEEE Trans. Parallel Distributed Syst., 2020

VFlow: More Expressive Generative Flows with Variational Data Augmentation.

Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Scalable Training of Hierarchical Topic Models.

Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu

Proc. VLDB Endow., 2018

Dropout training for SVMs with data augmentation.

Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen

Frontiers Comput. Sci., 2018

Stochastic Expectation Maximization with Variance Reduction.

Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stochastic Training of Graph Convolutional Networks with Variance Reduction.

Jianfei Chen, Jun Zhu, Le Song

Proceedings of the 35th International Conference on Machine Learning, 2018

Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems.

Zihao Xiao, Jianfei Chen, Jun Zhu

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Stochastic Training of Graph Convolutional Networks.

Jianfei Chen, Jun Zhu

CoRR, 2017

ZhuSuan: A Library for Bayesian Deep Learning.

Jiaxin Shi, Jianfei Chen, Jun Zhu, Shengyang Sun, Yucen Luo, Yihong Gu, Yuhao Zhou

CoRR, 2017

Scalable Inference for Nested Chinese Restaurant Process Topic Models.

Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu

CoRR, 2017

Population Matching Discrepancy and Applications in Deep Learning.

Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

TopicPanorama: A Full Picture of Relevant Topics.

Xiting Wang, Shixia Liu, Junlin Liu, Jianfei Chen, Jun Zhu, Baining Guo

IEEE Trans. Vis. Comput. Graph., 2016

WarpLDA: a Cache Efficient O(1) Algorithm for Latent Dirichlet Allocation.

Jianfei Chen, Kaiwei Li, Jun Zhu, Wenguang Chen

Proc. VLDB Endow., 2016

Streaming Gibbs Sampling for LDA Model.

Yang Gao, Jianfei Chen, Jun Zhu

CoRR, 2016

Scaling up Dynamic Topic Models.

Arnab Bhadury, Jianfei Chen, Jun Zhu, Shixia Liu

Proceedings of the 25th International Conference on World Wide Web, 2016

Distributing the Stochastic Gradient Sampler for Large-Scale LDA.

Yuan Yang, Jianfei Chen, Jun Zhu

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

WarpLDA: a Simple and Efficient O(1) Algorithm for Latent Dirichlet Allocation.

Jianfei Chen, Kaiwei Li, Jun Zhu, Wenguang Chen

CoRR, 2015

2014

Big Learning with Bayesian Methods.

Jun Zhu, Jianfei Chen, Wenbo Hu

CoRR, 2014

TopicPanorama: A full picture of relevant topics.

Shixia Liu, Xiting Wang, Jianfei Chen, Jim Zhu, Baining Guo

Proceedings of the 9th IEEE Conference on Visual Analytics Science and Technology, 2014

Bayesian Max-margin Multi-Task Learning with Data Augmentation.

Chengtao Li, Jun Zhu, Jianfei Chen

Proceedings of the 31th International Conference on Machine Learning, 2014

Dropout Training for Support Vector Machines.

Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Scalable Inference for Logistic-Normal Topic Models.

Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013