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Chongxuan Li
Chongxuan Li
Tenure-track Assistant Professor, Gaoling School of AI, Renmin University of China
Verified email at ruc.edu.cn - Homepage
Title
Cited by
Cited by
Year
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
4652016
Triple generative adversarial networks
C Li, K Xu, J Zhu, J Liu, B Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
457*2021
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
77*2017
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
582017
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
arXiv preprint arXiv:2206.00927, 2022
442022
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
422022
Graphical generative adversarial networks
C Li, M Welling, J Zhu, B Zhang
Advances in neural information processing systems 31, 2018
382018
Learning to generate with memory
C Li, J Zhu, B Zhang
International conference on machine learning, 1177-1186, 2016
362016
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
292018
Mice: Mixture of contrastive experts for unsupervised image clustering
TW Tsai, C Li, J Zhu
International conference on learning representations, 2021
282021
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
272021
Implicit normalizing flows
C Lu, J Chen, C Li, Q Wang, J Zhu
International Conference on Learning Representations, 2021
252021
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
22*2020
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
192020
Bayesian neural network realization by exploiting inherent stochastic characteristics of analog RRAM
Y Lin, Q Zhang, J Tang, B Gao, C Li, P Yao, Z Liu, J Zhu, J Lu, XS Hu, ...
2019 IEEE International Electron Devices Meeting (IEDM), 14.6. 1-14.6. 4, 2019
172019
Multi-objects generation with amortized structural regularization
T Xu, C Li, J Zhu, B Zhang
Advances in Neural Information Processing Systems 32, 2019
172019
Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations
M Zhao, F Bao, C Li, J Zhu
arXiv preprint arXiv:2207.06635, 2022
142022
To relieve your headache of training an mrf, take advil
C Li, C Du, K Xu, M Welling, J Zhu, B Zhang
International Conference on Learning Representations, 2019
14*2019
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, ...
arXiv preprint arXiv:2202.06592, 2022
122022
Learning implicit generative models by teaching density estimators
K Xu, C Du, C Li, J Zhu, B Zhang
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021
11*2021
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