Chongxuan Li

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	Visi	Nuo 2019
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h-rodyklė	30	29
i10-rodyklė	46	46

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Jun ZhuProfessor of Computer Science, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
fan baoShengShuPatvirtintas el. paštas shengshu.ai
Hang SuAssociated Professor, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
Cheng LuOpenAIPatvirtintas el. paštas openai.com
Kun XuTsinghua universityPatvirtintas el. paštas mails.tsinghua.edu.cn
Jianfei ChenAssociate Professor, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
Yuhao ZhouPh.D. Student, Tsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Chao DuSenior Research Scientist, Sea AI LabPatvirtintas el. paštas mails.tsinghua.edu.cn
Min ZhaoTsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
Shen NieRenmin University of ChinaPatvirtintas el. paštas ruc.edu.cn
Yue CaoLightyear AIPatvirtintas el. paštas baai.ac.cn
Kaiwen XueRenmin University of ChinaPatvirtintas el. paštas ruc.edu.cn
Zhengyi WangTsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Tianyu PangSenior Research Scientist, Sea AI LabPatvirtintas el. paštas sea.com
Lanqing HONGNational University of Singapore, Huawei Noah's Ark LabPatvirtintas el. paštas u.nus.edu
Guoqiang WuAssociate Professor, Shandong UniversityPatvirtintas el. paštas sdu.edu.cn
Liyuan WangTsinghua UniversityPatvirtintas el. paštas mails.tsinghua.edu.cn
Jiaxin ShiResearch Scientist, Google DeepMindPatvirtintas el. paštas google.com
Chenyu ZhengRenmin University of ChinaPatvirtintas el. paštas ruc.edu.cn
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamPatvirtintas el. paštas uva.nl

Stebėti

Chongxuan Li

Associate Professor (tenure track), Renmin University of China

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

Machine Learning Generative Models Deep Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	893	2022
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	602	2016
Triple generative adversarial nets C Li, T Xu, J Zhu, B Zhang Advances in neural information processing systems 30, 2017	558	2017
Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation Z Wang, C Lu, Y Wang, F Bao, C Li, H Su, J Zhu Advances in Neural Information Processing Systems 36, 2024	514	2024
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	333	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	297	2022
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	230*	2023
Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations M Zhao, F Bao, C Li, J Zhu NeurIPS 2022, 2022	169	2022
On evaluating adversarial robustness of large vision-language models Y Zhao, T Pang, C Du, X Yang, C Li, NMM Cheung, M Lin Advances in Neural Information Processing Systems 36, 2024	110	2024
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale F Bao, S Nie, K Xue, C Li, S Pu, Y Wang, G Yue, Y Cao, H Su, J Zhu ICML, 2023, 2023	108	2023
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	105	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	90	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	82	2021
Mice: Mixture of contrastive experts for unsupervised image clustering TW Tsai, C Li, J Zhu International conference on learning representations, 2020	82	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	71	2022
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	66	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	53	2017
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	49	2020
Equivariant Energy-Guided SDE for Inverse Molecular Design F Bao, M Zhao, Z Hao, P Li, C Li, J Zhu ICLR 2023, 2022	47	2022
Learning to generate with memory C Li, J Zhu, B Zhang International conference on machine learning, 1177-1186, 2016	47	2016

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