Zhanxing Zhu

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Bing YuPeking UniversityVerified email at pku.edu.cn
Lei Wu (吴磊)Assistant Professor, Peking UniversityVerified email at math.pku.edu.cn
Haoyi XiongBaidu, Inc.; previously MST, UVA, TSP/UPMCVerified email at baidu.com
Haoteng YINPurdue UniversityVerified email at purdue.edu
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR & CSIG; ex-VP of Samsung ResearchVerified email at pku.edu.cn
Ke SunUniversity of Alberta, Peking UniversityVerified email at ualberta.ca
Ju XuPeking UniversityVerified email at pku.edu.cn
Dinghuai ZhangMilaVerified email at mila.quebec
Jun (Luke) HuanAWS AI LabsVerified email at amazon.com
Yansong FengPeking UniversityVerified email at pku.edu.cn
Ruosi WanHong Kong University of Science and TechnologyVerified email at connect.ust.hk
Tianyuan ZhangCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Amos StorkeyProfessor of Machine Learning and AI, School of Informatics, University of Edinburgh, UKVerified email at ed.ac.uk
Zheng WangProfessor of Intelligent Software Technology, University of LeedsVerified email at leeds.ac.uk
Mengzhang LiPeking UniversityVerified email at pku.edu.cn
Jingfeng WuJohns Hopkins UniversityVerified email at jhu.edu
Wenqing HuMissouri University of Science and Technology (formerly University of Missouri, Rolla)Verified email at mst.edu
Francesco CoronaAalto UniversityVerified email at aalto.fi
Bin DongBeijing International Center for Mathematical Research, Peking UniversityVerified email at math.pku.edu.cn
Yiping LuStanford UniversityVerified email at stanford.edu

Zhanxing Zhu

Unknown affiliation

Verified email at pku.edu.cn - Homepage

Deep learning large-scale optimization Bayesian methods.


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Spatio-temporal graph convolutional neural network: A deep learning framework for traffic forecasting B Yu, H Yin, Z Zhu International Joint Conference of Artificial Intelligence (IJCAI 2018), 2018	1436*	2018
You only propagate once: Accelerating adversarial training via maximal principle D Zhang, T Zhang, Y Lu, Z Zhu, B Dong Advances in Neural Information Processing Systems, 2019, 2019	254	2019
Reinforced continual learning J Xu, Z Zhu Advances in Neural Information Processing Systems (NeurIPS 2018), 899-908, 2018	165	2018
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects Z Zhu, J Wu, B Yu, L Wu, J Ma International Conference on Machine Learning (ICML 2019), 7654-7663, 2019	143	2019
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes L Wu, Z Zhu The 34th International Conference on Machine Learning (ICML 2017 …, 2017	137	2017
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes. K Sun, Z Lin, Z Zhu AAAI 2020, 5892-5899, 2020	122	2020
Yet another text captcha solver: A generative adversarial network based approach G Ye, Z Tang, D Fang, Z Zhu, Y Feng, P Xu, X Chen, Z Wang Proceedings of the 2018 ACM SIGSAC conference on computer and communications …, 2018	98	2018
Novel subgroups of patients with adult-onset diabetes in Chinese and US populations X Zou, X Zhou, Z Zhu, L Ji The Lancet Diabetes & Endocrinology 7 (1), 9-11, 2019	94	2019
Interpreting Adversarially Trained Convolutional Neural Networks T Zhang, Z Zhu International Conference on Machine Learning (ICML 2019), 2019	93	2019
Spatial-temporal fusion graph neural networks for traffic flow forecasting M Li, Z Zhu AAAI 2021, 2020	78	2020
Learning with noise: Enhance distantly supervised relation extraction with dynamic transition matrix B Luo, Y Feng, Z Wang, Z Zhu, S Huang, R Yan, D Zhao ACL 2017, 2017	77	2017
Towards understanding and improving the transferability of adversarial examples in deep neural networks L Wu, Z Zhu Asian Conference on Machine Learning, 837-850, 2020	76*	2020
Efficient Neural Architecture Search via Proximal Iterations. Q Yao, J Xu, WW Tu, Z Zhu AAAI 2020, 6664-6671, 2020	70*	2020
Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling X Shang, Z Zhu, B Leimkuhler, AJ Storkey NIPS 2015, 2015	48	2015
Spatio-temporal manifold learning for human motions via long-horizon modeling H Wang, ESL Ho, HPH Shum, Z Zhu IEEE transactions on visualization and computer graphics 27 (1), 216-227, 2019	43	2019
3d graph convolutional networks with temporal graphs: A spatial information free framework for traffic forecasting B Yu, M Li, J Zhang, Z Zhu arXiv preprint arXiv:1903.00919, 2019	41	2019
St-unet: A spatio-temporal u-network for graph-structured time series modeling B Yu, H Yin, Z Zhu arXiv preprint arXiv:1903.05631, 2019	39	2019
On the Noisy Gradient Descent that Generalizes as SGD J Wu, W Hu, H Xiong, J Huan, V Braverman, Z Zhu International Conference for Machine Learning (ICML 2020), 2020	37	2020
Bayesian adversarial learning N Ye, Z Zhu Advances in Neural Information Processing Systems 31, 2018	34	2018
A deep learning-based framework for conducting stealthy attacks in industrial control systems C Feng, T Li, Z Zhu, D Chana arXiv preprint arXiv:1709.06397, 2017	34	2017

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