Chongxuan Li

Cituota

	Visi	Nuo 2018
Šaltiniai	2303	2205
h-rodyklė	20	20
i10-rodyklė	31	31

820

410

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615

2016201720182019202020212022202316 68 158 208 269 319 441 806

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Jun ZhuProfessor of Computer Science, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
fan baoTsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Kun XuTsinghua universityPatvirtintas el. paštas mails.tsinghua.edu.cn
Jianfei ChenAssistant Professor, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
Hang SuAssociated Professor, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
Cheng LuTsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Chao DuResearch Scientist, Sea AI LabPatvirtintas el. paštas mails.tsinghua.edu.cn
Lanqing HONGNational University of Singapore, Huawei Noah's Ark LabPatvirtintas el. paštas u.nus.edu
Mengchen LiuMicrosoftPatvirtintas el. paštas microsoft.com
Jiaxin ShiResearch Scientist, Google DeepMindPatvirtintas el. paštas google.com
Yue CaoBeijing Academy of Artificial IntelligencePatvirtintas el. paštas baai.ac.cn
Liyuan WangTsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Max WellingDistinguished Scientist at MSR AI4Science & Professor Machine Learning, University of AmsterdamPatvirtintas el. paštas uva.nl
Guoqiang WuAssociate Professor, Shandong UniversityPatvirtintas el. paštas sdu.edu.cn
Tianyu PangResearch Scientist, Sea AI LabPatvirtintas el. paštas sea.com
yong zhongRenmin University of China, Gaoling School of Artificial IntelligencePatvirtintas el. paštas ruc.edu.cn
Zhengyi WangTsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Zebin Yourenmin university of chinaPatvirtintas el. paštas ruc.edu.cn

Stebėti

Chongxuan Li

Associate Professor, Renmin University of China

Patvirtintas el. paštas ruc.edu.cn - Pagrindinis puslapis

Machine Learning Deep Generative Models


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Towards better analysis of deep convolutional neural networks M Liu, J Shi, Z Li, C Li, J Zhu, S Liu IEEE transactions on visualization and computer graphics 23 (1), 91-100, 2016	519	2016
Triple generative adversarial networks C Li, K Xu, J Zhu, J Liu, B Zhang IEEE transactions on pattern analysis and machine intelligence 44 (12), 9629 …, 2021	512*	2021
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 NeurIPS 2022, 2022	227	2022
Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models F Bao, C Li, J Zhu, B Zhang International Conference on Learning Representations, 2022	131	2022
Learning to write stylized chinese characters by reading a handful of examples D Sun, T Ren, C Li, H Su, J Zhu arXiv preprint arXiv:1712.06424, 2017	70	2017
Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations M Zhao, F Bao, C Li, J Zhu NeurIPS 2022, 2022	59	2022
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	58	2022
Max-margin deep generative models for (semi-) supervised learning C Li, J Zhu, B Zhang IEEE transactions on pattern analysis and machine intelligence 40 (11), 2762 …, 2017	48	2017
Ordisco: Effective and efficient usage of incremental unlabeled data for semi-supervised continual learning L Wang, K Yang, C Li, L Hong, Z Li, J Zhu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	46	2021
Learning to generate with memory C Li, J Zhu, B Zhang International conference on machine learning, 1177-1186, 2016	42	2016
Memory replay with data compression for continual learning L Wang, X Zhang, K Yang, L Yu, C Li, L Hong, S Zhang, Z Li, Y Zhong, ... ICLR 2022, 2022	41	2022
Graphical generative adversarial networks C Li, M Welling, J Zhu, B Zhang Advances in neural information processing systems 31, 2018	41	2018
Mice: Mixture of contrastive experts for unsupervised image clustering TW Tsai, C Li, J Zhu International conference on learning representations, 2020	38	2020
Estimating the optimal covariance with imperfect mean in diffusion probabilistic models F Bao, C Li, J Sun, J Zhu, B Zhang arXiv preprint arXiv:2206.07309, 2022	36	2022
Collaborative filtering with user-item co-autoregressive models C Du, C Li, Y Zheng, J Zhu, B Zhang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	36	2018
Max-margin deep generative models C Li, J Zhu, T Shi, B Zhang Advances in neural information processing systems 28, 2015	36	2015
All are worth words: A vit backbone for diffusion models F Bao, S Nie, K Xue, Y Cao, C Li, H Su, J Zhu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	32*	2023
Efficient learning of generative models via finite-difference score matching T Pang, K Xu, C Li, Y Song, S Ermon, J Zhu Advances in Neural Information Processing Systems 33, 19175-19188, 2020	31	2020
Implicit normalizing flows C Lu, J Chen, C Li, Q Wang, J Zhu International Conference on Learning Representations, 2021	30	2021
Understanding and stabilizing GANs’ training dynamics using control theory K Xu, C Li, J Zhu, B Zhang International Conference on Machine Learning, 10566-10575, 2020	30*	2020

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