Zhanxing Zhu

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Bing YuXiaohongshuAdresse e-mail validée de pku.edu.cn
Lei Wu (吴磊)Assistant Professor, Peking UniversityAdresse e-mail validée de math.pku.edu.cn
Haoyi XiongMicrosoftAdresse e-mail validée de microsoft.com
Haoteng YINPurdue UniversityAdresse e-mail validée de purdue.edu
Ju XuPeking UniversityAdresse e-mail validée de pku.edu.cn
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR, CSIG & AAIA; ex-VP of Samsung ResearchAdresse e-mail validée de pku.edu.cn
Ke Sun (孙科)Postdoc, Harvard UniversityAdresse e-mail validée de fas.harvard.edu
Dinghuai Zhang 张鼎怀Microsoft Research / MilaAdresse e-mail validée de mila.quebec
Mengzhang LiShanghai AI LabAdresse e-mail validée de pku.edu.cn
Jun (Luke) HuanAWS AI LabsAdresse e-mail validée de amazon.com
Yansong FengPeking UniversityAdresse e-mail validée de pku.edu.cn
Ruosi WanHong Kong University of Science and TechnologyAdresse e-mail validée de connect.ust.hk
Tianyuan ZhangMITAdresse e-mail validée de mit.edu
Zheng WangProfessor of Intelligent Software Technology, University of LeedsAdresse e-mail validée de leeds.ac.uk
Amos StorkeyProfessor of Machine Learning and AI, School of Informatics, University of Edinburgh, UKAdresse e-mail validée de ed.ac.uk
Wenqing HuMissouri University of Science and Technology (formerly University of Missouri, Rolla)Adresse e-mail validée de mst.edu
Jingfeng WuUniversity of California, BerkeleyAdresse e-mail validée de berkeley.edu
He WANG (王鹤)Associate Professor, Department of Computer Science, University College London, UKAdresse e-mail validée de ucl.ac.uk
Bin DongBeijing International Center for Mathematical Research, Peking UniversityAdresse e-mail validée de math.pku.edu.cn
Yiping LuAssistant Professor, Northwestern UniversityAdresse e-mail validée de northwestern.edu

Suivre

Zhanxing Zhu

Associate Professor, ECS, University of Southampton

Adresse e-mail validée de soton.ac.uk - Page d'accueil

Deep learning robust and trustworthy machine learning time series AI for Science


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	4680*	2018
Spatial-temporal fusion graph neural networks for traffic flow forecasting M Li, Z Zhu AAAI 2021, 2020	832	2020
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	493	2019
Reinforced continual learning J Xu, Z Zhu Advances in Neural Information Processing Systems (NeurIPS 2018), 899-908, 2018	429	2018
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	285	2020
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	249	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	227	2017
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	226	2019
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	179*	2020
Interpreting Adversarially Trained Convolutional Neural Networks T Zhang, Z Zhu International Conference on Machine Learning (ICML 2019), 2019	178	2019
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	174	2018
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective B Shi, D Zhang, Q Dai, Z Zhu, Y Mu, J Wang International Conference for Machine Learning (ICML 2020), 2020	125	2020
Efficient Neural Architecture Search via Proximal Iterations. Q Yao, J Xu, WW Tu, Z Zhu AAAI 2020, 6664-6671, 2020	124	2020
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	115	2020
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models K Sun, Z Zhu, Z Lin ICLR 2021, 2021	107	2021
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	105	2017
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	88	2019
Automatic data augmentation for 3D medical image segmentation J Xu, M Li, Z Zhu Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020	81	2020
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	79	2019
Black-box certification with randomized smoothing: A functional optimization based framework D Zhang, M Ye, C Gong, Z Zhu, Q Liu NeurIPS 2020, 2020	75	2020

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