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Jianfei Chen 0001
Person information
- unicode name: 陈键飞
- affiliation: Tsinghua University, Beijing, China
Other persons with the same name
- Jianfei Chen — disambiguation page
- Jianfei Chen 0002 — Xi'an Jiaotong University, China
- Jianfei Chen 0003
— Nanjing University of Posts and Telecommunications, School of Optoelectronic Engineering, China
- Jianfei Chen 0004
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2020 – today
- 2024
- [i25]Tianjiao Luo, Tim Pearce, Huayu Chen, Jianfei Chen, Jun Zhu:
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory. CoRR abs/2402.16349 (2024) - [i24]Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu:
Diffusion Bridge Implicit Models. CoRR abs/2405.15885 (2024) - [i23]Guande He, Kaiwen Zheng, Jianfei Chen, Fan Bao, Jun Zhu:
Consistency Diffusion Bridge Models. CoRR abs/2410.22637 (2024) - 2023
- [c19]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: 22825-22855 - [c18]Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu:
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs. ICML 2023: 42363-42389 - [c17]Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu:
DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics. NeurIPS 2023 - [i22]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 abs/2304.12824 (2023) - [i21]Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu:
Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs. CoRR abs/2305.03935 (2023) - [i20]Bingrui Li, Jianfei Chen, Jun Zhu:
Memory Efficient Optimizers with 4-bit States. CoRR abs/2309.01507 (2023) - [i19]Guande He, Peng Cui, Jianfei Chen, Wenbo Hu, Jun Zhu:
Investigating Uncertainty Calibration of Aligned Language Models under the Multiple-Choice Setting. CoRR abs/2310.11732 (2023) - [i18]Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu:
DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics. CoRR abs/2310.13268 (2023) - 2022
- [c16]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: 14429-14460 - [c15]Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang:
Fast Lossless Neural Compression with Integer-Only Discrete Flows. ICML 2022: 22562-22575 - [c14]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 - [i17]Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu:
Deep Ensemble as a Gaussian Process Approximate Posterior. CoRR abs/2205.00163 (2022) - [i16]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 abs/2206.00927 (2022) - [i15]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 abs/2206.08265 (2022) - [i14]Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang:
Fast Lossless Neural Compression with Integer-Only Discrete Flows. CoRR abs/2206.08869 (2022) - [i13]Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu:
DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. CoRR abs/2211.01095 (2022) - 2021
- [c13]Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu:
Implicit Normalizing Flows. ICLR 2021 - [i12]Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu:
Implicit Normalizing Flows. CoRR abs/2103.09527 (2021) - 2020
- [j5]Kaiwei Li
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. IEEE Trans. Parallel Distributed Syst. 31(9): 2112-2124 (2020) - [c12]Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian:
VFlow: More Expressive Generative Flows with Variational Data Augmentation. ICML 2020: 1660-1669 - [i11]Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian:
VFlow: More Expressive Generative Flows with Variational Data Augmentation. CoRR abs/2002.09741 (2020)
2010 – 2019
- 2018
- [j4]Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen:
Dropout training for SVMs with data augmentation. Frontiers Comput. Sci. 12(4): 694-713 (2018) - [j3]Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu
Scalable Training of Hierarchical Topic Models. Proc. VLDB Endow. 11(7): 826-839 (2018) - [c11]Zihao Xiao, Jianfei Chen, Jun Zhu:
Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems. AAAI 2018: 6459-6467 - [c10]Jianfei Chen, Jun Zhu, Le Song:
Stochastic Training of Graph Convolutional Networks with Variance Reduction. ICML 2018: 941-949 - [c9]Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang:
Stochastic Expectation Maximization with Variance Reduction. NeurIPS 2018: 7978-7988 - [i10]Zihao Xiao, Jianfei Chen, Jun Zhu:
Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems. CoRR abs/1804.03578 (2018) - 2017
- [c8]Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu:
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. ASPLOS 2017: 497-509 - [c7]Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu:
Population Matching Discrepancy and Applications in Deep Learning. NIPS 2017: 6262-6272 - [i9]Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu:
Scalable Inference for Nested Chinese Restaurant Process Topic Models. CoRR abs/1702.07083 (2017) - [i8]Jiaxin Shi, Jianfei Chen, Jun Zhu, Shengyang Sun, Yucen Luo, Yihong Gu, Yuhao Zhou:
ZhuSuan: A Library for Bayesian Deep Learning. CoRR abs/1709.05870 (2017) - [i7]Jianfei Chen, Jun Zhu:
Stochastic Training of Graph Convolutional Networks. CoRR abs/1710.10568 (2017) - 2016
- [j2]Jianfei Chen, Kaiwei Li, Jun Zhu, Wenguang Chen:
WarpLDA: a Cache Efficient O(1) Algorithm for Latent Dirichlet Allocation. Proc. VLDB Endow. 9(10): 744-755 (2016) - [j1]Xiting Wang, Shixia Liu
TopicPanorama: A Full Picture of Relevant Topics. IEEE Trans. Vis. Comput. Graph. 22(12): 2508-2521 (2016) - [c6]Yuan Yang, Jianfei Chen, Jun Zhu:
Distributing the Stochastic Gradient Sampler for Large-Scale LDA. KDD 2016: 1975-1984 - [c5]Arnab Bhadury, Jianfei Chen, Jun Zhu, Shixia Liu
Scaling up Dynamic Topic Models. WWW 2016: 381-390 - [i6]Yang Gao, Jianfei Chen, Jun Zhu:
Streaming Gibbs Sampling for LDA Model. CoRR abs/1601.01142 (2016) - [i5]Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu:
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs. CoRR abs/1610.02496 (2016) - 2015
- [i4]Ning Chen, Jun Zhu, Jianfei Chen, Ting Chen:
Dropout Training for SVMs with Data Augmentation. CoRR abs/1508.02268 (2015) - [i3]Jianfei Chen, Kaiwei Li, Jun Zhu, Wenguang Chen:
WarpLDA: a Simple and Efficient O(1) Algorithm for Latent Dirichlet Allocation. CoRR abs/1510.08628 (2015) - 2014
- [c4]Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang:
Dropout Training for Support Vector Machines. AAAI 2014: 1752-1759 - [c3]Chengtao Li, Jun Zhu, Jianfei Chen:
Bayesian Max-margin Multi-Task Learning with Data Augmentation. ICML 2014: 415-423 - [c2]Shixia Liu
TopicPanorama: A full picture of relevant topics. IEEE VAST 2014: 183-192 - [i2]Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang:
Dropout Training for Support Vector Machines. CoRR abs/1404.4171 (2014) - [i1]Jun Zhu, Jianfei Chen, Wenbo Hu:
Big Learning with Bayesian Methods. CoRR abs/1411.6370 (2014) - 2013
- [c1]Jianfei Chen, Jun Zhu, Zi Wang, Xun Zheng, Bo Zhang:
Scalable Inference for Logistic-Normal Topic Models. NIPS 2013: 2445-2453
Coauthor Index
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