Jianfei Chen

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Jun ZhuProfessor of Computer Science, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
Cheng LuOpenAIVerified email at openai.com
Chongxuan LiAssociate Professor (tenure track), Renmin University of ChinaVerified email at ruc.edu.cn
fan baoShengShuVerified email at shengshu.ai
Yuhao ZhouPh.D. Student, Tsinghua UniversityVerified email at mails.tsinghua.edu.cn
Tang JieWeBank Chair Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Weize ChenTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Zhiyuan LiuAssociate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Shixia LiuProfessor, Tsinghua University, IEEE FellowVerified email at tsinghua.edu.cn
Shengding HuTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Maosong SunProfessor of Computer Science and Technology, Tsinghua UniversityVerified email at tsinghua.edu.cn
Joseph E. GonzalezProfessor of Computer Science, UC BerkeleyVerified email at berkeley.edu
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Michael MahoneyProfessor of Statistics, UC BerkeleyVerified email at stat.berkeley.edu
Kaiwei LiTsinghua UniversityVerified email at mails.tsinghua.edu.cn
Baining GuoDistinguished Scientist, Microsoft ResearchVerified email at microsoft.com
Xiting WangAssistant Professor, Renmin University of ChinaVerified email at ruc.edu.cn
Dequan WangShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
Zhewei YaoSnowflakeVerified email at snowflake.com
Wenbo HuHefei University of TechnologyVerified email at hfut.edu.cn

Jianfei Chen

Associate Professor, Tsinghua University

Verified email at mail.tsinghua.edu.cn - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps C Lu, Y Zhou, F Bao, J Chen, C Li, J Zhu Advances in Neural Information Processing Systems 35, 5775-5787, 2022	866	2022
Stochastic Training of Graph Convolutional Networks with Variance Reduction. J Chen, J Zhu, L Song ICML, 941-949, 2018	610	2018
Parameter-efficient fine-tuning of large-scale pre-trained language models N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su, S Hu, Y Chen, CM Chan, ... Nature Machine Intelligence 5 (3), 220-235, 2023	424	2023
Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models C Lu, Y Zhou, F Bao, J Chen, C Li, J Zhu arXiv preprint arXiv:2211.01095, 2022	320	2022
Delta tuning: A comprehensive study of parameter efficient methods for pre-trained language models N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su, S Hu, Y Chen, CM Chan, ... arXiv preprint arXiv:2203.06904, 2022	201	2022
Topicpanorama: a full picture of relevant topics S Liu, X Wang, J Chen, J Zhu, B Guo IEEE Transactions on Visualization and Computer Graphics 20, 12, 2014	121	2014
Scalable inference for logistic-normal topic models J Chen, J Zhu, Z Wang, X Zheng, B Zhang Advances in neural information processing systems 26, 2013	95	2013
Big learning with Bayesian methods J Zhu, J Chen, W Hu, B Zhang National Science Review 4 (4), 627-651, 2017	93	2017
Warplda: a cache efficient o (1) algorithm for latent dirichlet allocation J Chen, K Li, J Zhu, W Chen arXiv preprint arXiv:1510.08628, 2015	93	2015
Scaling up dynamic topic models A Bhadury, J Chen, J Zhu, S Liu Proceedings of the 25th International Conference on World Wide Web, 381-390, 2016	89	2016
TopicPanorama: A full picture of relevant topics X Wang, S Liu, J Liu, J Chen, J Zhu, B Guo IEEE transactions on visualization and computer graphics 22 (12), 2508-2521, 2016	72	2016
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training J Chen, L Zheng, Z Yao, D Wang, I Stoica, MW Mahoney, JE Gonzalez International Conference on Machine Learning, 2021	67	2021
Maximum likelihood training for score-based diffusion odes by high order denoising score matching C Lu, K Zheng, F Bao, J Chen, C Li, J Zhu International Conference on Machine Learning, 14429-14460, 2022	65	2022
Stochastic Expectation Maximization with Variance Reduction J Chen, J Zhu, YW Teh, T Zhang Advances in Neural Information Processing Systems, 7978-7988, 2018	65	2018
Vflow: More expressive generative flows with variational data augmentation J Chen, C Lu, B Chenli, J Zhu, T Tian International Conference on Machine Learning, 1660-1669, 2020	63	2020
Bev-seg: Bird's eye view semantic segmentation using geometry and semantic point cloud MH Ng, K Radia, J Chen, D Wang, I Gog, JE Gonzalez arXiv preprint arXiv:2006.11436, 2020	62	2020
ZhuSuan: A library for Bayesian deep learning J Shi, J Chen, J Zhu, S Sun, Y Luo, Y Gu, Y Zhou arXiv preprint arXiv:1709.05870, 2017	47	2017
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks J Chen, Y Gai, Z Yao, MW Mahoney, JE Gonzalez Advances in Neural Information Processing Systems, 2020	41	2020
Dropout Training for Support Vector Machines. N Chen, J Zhu, J Chen, B Zhang AAAI, 1752-1759, 2014	40	2014
Contrastive energy prediction for exact energy-guided diffusion sampling in offline reinforcement learning C Lu, H Chen, J Chen, H Su, C Li, J Zhu International Conference on Machine Learning, 22825-22855, 2023	38	2023

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