Zhanxing Zhu
Zhanxing Zhu
Zugehörigkeit unbekannt
Bestätigte E-Mail-Adresse bei pku.edu.cn - Startseite
Zitiert von
Zitiert von
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
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
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes
L Wu, Z Zhu
The 34th International Conference on Machine Learning (ICML 2017 …, 2017
Reinforced continual learning
J Xu, Z Zhu
Advances in Neural Information Processing Systems (NeurIPS 2018), 899-908, 2018
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
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
The anisotropic noise in stochastic gradient descent: Its behavior of escaping from minima and regularization effects
Z Zhu, J Wu, B Yu, L Wu, J Ma
Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling
X Shang, Z Zhu, B Leimkuhler, AJ Storkey
arXiv preprint arXiv:1510.08692, 2015
Interpreting Adversarially Trained Convolutional Neural Networks
T Zhang, Z Zhu
International Conference on Machine Learning (ICML 2019), 2019
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
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
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
Efficient Neural Architecture Search via Proximal Iterations.
Q Yao, J Xu, WW Tu, Z Zhu
AAAI 2020, 6664-6671, 2020
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
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
Adaptive stochastic primal-dual coordinate descent for separable saddle point problems
Z Zhu, AJ Storkey
Joint European Conference on Machine Learning and Knowledge Discovery in …, 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
Bayesian adversarial learning
N Ye, Z Zhu
Proceedings of the 32nd International Conference on Neural Information …, 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
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
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20