Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDChongxuan Li
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2023
[i41]Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu:
Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. CoRR abs/2302.02334 (2023)- [i40]Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu:
Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. CoRR abs/2302.10586 (2023) - [i39]Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu:
One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. CoRR abs/2303.06555 (2023) - [i38]Chendong Xiang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu:
A Closer Look at Parameter-Efficient Tuning in Diffusion Models. CoRR abs/2303.18181 (2023) - [i37]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) - [i36]Guoqiang Wu, Chongxuan Li, Yilong Yin:
Towards Understanding Generalization of Macro-AUC in Multi-label Learning. CoRR abs/2305.05248 (2023) - 2022
- [j4]Chongxuan Li
, Kun Xu, Jun Zhu, Jiashuo Liu, Bo Zhang:
Triple Generative Adversarial Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9629-9640 (2022) - [j3]Dong Yan, Jiayi Weng, Shiyu Huang, Chongxuan Li, Yichi Zhou, Hang Su, Jun Zhu:
Deep reinforcement learning with credit assignment for combinatorial optimization. Pattern Recognit. 124: 108466 (2022) - [c26]Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang:
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. ICLR 2022 - [c25]Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu:
Memory Replay with Data Compression for Continual Learning. ICLR 2022 - [c24]Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang:
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. ICML 2022: 1555-1584 - [c23]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 - [c22]Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang:
Fast Lossless Neural Compression with Integer-Only Discrete Flows. ICML 2022: 22562-22575 - [c21]Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu:
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. NeurIPS 2022 - [c20]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 - [i35]Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang:
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. CoRR abs/2201.06503 (2022) - [i34]Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu:
Memory Replay with Data Compression for Continual Learning. CoRR abs/2202.06592 (2022) - [i33]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) - [i32]Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang:
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. CoRR abs/2206.07309 (2022) - [i31]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) - [i30]Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang:
Fast Lossless Neural Compression with Integer-Only Discrete Flows. CoRR abs/2206.08869 (2022) - [i29]Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu:
EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. CoRR abs/2207.06635 (2022) - [i28]Yong Zhong, Hongtao Liu, Xiaodong Liu, Fan Bao, Weiran Shen, Chongxuan Li:
Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models. CoRR abs/2208.14133 (2022) - [i27]Fan Bao, Chongxuan Li, Yue Cao, Jun Zhu:
All are Worth Words: a ViT Backbone for Score-based Diffusion Models. CoRR abs/2209.12152 (2022) - [i26]Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu:
Equivariant Energy-Guided SDE for Inverse Molecular Design. CoRR abs/2209.15408 (2022) - [i25]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) - [i24]Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu:
Why Are Conditional Generative Models Better Than Unconditional Ones? CoRR abs/2212.00362 (2022) - 2021
- [c19]Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu:
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning. CVPR 2021: 5383-5392 - [c18]Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu:
Implicit Normalizing Flows. ICLR 2021 - [c17]Tsung Wei Tsai, Chongxuan Li, Jun Zhu:
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. ICLR 2021 - [c16]Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang:
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. ICML 2021: 651-661 - [c15]Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang:
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. NeurIPS 2021: 4529-4541 - [c14]Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu:
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. NeurIPS 2021: 14332-14344 - [i23]Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu:
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning. CoRR abs/2101.00407 (2021) - [i22]Qijun Luo, Zhili Liu, Lanqing Hong, Chongxuan Li, Kuo Yang, Liyuan Wang, Fengwei Zhou, Guilin Li, Zhenguo Li, Jun Zhu:
Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation. CoRR abs/2101.01400 (2021) - [i21]Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu:
Implicit Normalizing Flows. CoRR abs/2103.09527 (2021) - [i20]Tsung Wei Tsai, Chongxuan Li, Jun Zhu:
MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. CoRR abs/2105.01899 (2021) - [i19]Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu:
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. CoRR abs/2105.05026 (2021) - [i18]Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang:
Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. CoRR abs/2106.04188 (2021) - 2020
- [c13]Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang:
To Relieve Your Headache of Training an MRF, Take AdVIL. ICLR 2020 - [c12]Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang:
Understanding and Stabilizing GANs' Training Dynamics Using Control Theory. ICML 2020: 10566-10575 - [c11]Fan Bao, Chongxuan Li, Taufik Xu, Hang Su, Jun Zhu, Bo Zhang:
Bi-level Score Matching for Learning Energy-based Latent Variable Models. NeurIPS 2020 - [c10]Tianyu Pang, Taufik Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu:
Efficient Learning of Generative Models via Finite-Difference Score Matching. NeurIPS 2020 - [c9]Kun Xu, Chao Du, Chongxuan Li, Jun Zhu, Bo Zhang:
Learning Implicit Generative Models by Teaching Density Estimators. ECML/PKDD (2) 2020: 239-255 - [i17]Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu:
Efficient Learning of Generative Models via Finite-Difference Score Matching. CoRR abs/2007.03317 (2020) - [i16]Fan Bao, Chongxuan Li, Kun Xu, Hang Su, Jun Zhu, Bo Zhang:
Bi-level Score Matching for Learning Energy-based Latent Variable Models. CoRR abs/2010.07856 (2020) - [i15]Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang:
Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. CoRR abs/2010.08258 (2020)
2010 – 2019
- 2019
- [c8]Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang:
Multi-objects Generation with Amortized Structural Regularization. NeurIPS 2019: 6615-6625 - [i14]Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang:
Adversarial Variational Inference and Learning in Markov Random Fields. CoRR abs/1901.08400 (2019) - [i13]Tsung Wei Tsai, Chongxuan Li, Jun Zhu:
DS3L: Deep Self-Semi-Supervised Learning for Image Recognition. CoRR abs/1905.13305 (2019) - [i12]Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang:
Multi-objects Generation with Amortized Structural Regularization. CoRR abs/1906.03923 (2019) - [i11]Kun Xu, Chongxuan Li, Huanshu Wei, Jun Zhu, Bo Zhang:
Understanding and Stabilizing GANs' Training Dynamics with Control Theory. CoRR abs/1909.13188 (2019) - [i10]Chongxuan Li, Kun Xu, Jiashuo Liu, Jun Zhu, Bo Zhang:
Triple Generative Adversarial Networks. CoRR abs/1912.09784 (2019) - 2018
- [j2]Chongxuan Li, Jun Zhu, Bo Zhang:
Max-Margin Deep Generative Models for (Semi-)Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 40(11): 2762-2775 (2018) - [c7]Chao Du, Chongxuan Li, Yin Zheng, Jun Zhu, Bo Zhang:
Collaborative Filtering With User-Item Co-Autoregressive Models. AAAI 2018: 2175-2182 - [c6]Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu:
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. IJCAI 2018: 920-927 - [c5]Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang:
Graphical Generative Adversarial Networks. NeurIPS 2018: 6072-6083 - [i9]Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang:
Graphical Generative Adversarial Networks. CoRR abs/1804.03429 (2018) - [i8]Chao Du, Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang:
Learning Implicit Generative Models by Teaching Explicit Ones. CoRR abs/1807.03870 (2018) - 2017
- [j1]Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu:
Towards Better Analysis of Deep Convolutional Neural Networks. IEEE Trans. Vis. Comput. Graph. 23(1): 91-100 (2017) - [c4]Chongxuan Li, Taufik Xu, Jun Zhu, Bo Zhang:
Triple Generative Adversarial Nets. NIPS 2017: 4088-4098 - [c3]Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu:
Population Matching Discrepancy and Applications in Deep Learning. NIPS 2017: 6262-6272 - [i7]Chongxuan Li, Kun Xu, Jun Zhu, Bo Zhang:
Triple Generative Adversarial Nets. CoRR abs/1703.02291 (2017) - [i6]Danyang Sun, Tongzheng Ren, Chongxuan Li, Jun Zhu, Hang Su:
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. CoRR abs/1712.06424 (2017) - 2016
- [c2]Chongxuan Li, Jun Zhu, Bo Zhang:
Learning to Generate with Memory. ICML 2016: 1177-1186 - [i5]Chongxuan Li, Jun Zhu, Bo Zhang:
Learning to Generate with Memory. CoRR abs/1602.07416 (2016) - [i4]Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu:
Towards Better Analysis of Deep Convolutional Neural Networks. CoRR abs/1604.07043 (2016) - [i3]Chongxuan Li, Jun Zhu, Bo Zhang:
Max-Margin Deep Generative Models for (Semi-)Supervised Learning. CoRR abs/1611.07119 (2016) - [i2]Chao Du, Chongxuan Li, Yin Zheng, Jun Zhu, Cailiang Liu, Hanning Zhou, Bo Zhang:
Collaborative Filtering with User-Item Co-Autoregressive Models. CoRR abs/1612.07146 (2016) - 2015
- [c1]Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang:
Max-Margin Deep Generative Models. NIPS 2015: 1837-1845 - [i1]Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang:
Max-margin Deep Generative Models. CoRR abs/1504.06787 (2015)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
load content from web.archive.org
Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2023-05-13 23:17 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
