Zhijie Deng
Zhijie Deng
Other names邓 志杰
Tenure-track Assistant Professor, Shanghai Jiao Tong University
Verified email at - Homepage
Cited by
Cited by
Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
Z Deng, Y Luo, J Zhu
IEEE International Conference on Computer Vision 2019, 2019
Adversarial distributional training for robust deep learning
Y Dong, Z Deng, T Pang, H Su, J Zhu
Advances in Neural Information Processing Systems 33, 2020
Batch Virtual Adversarial Training for Graph Convolutional Networks
Z Deng, Y Dong, J Zhu
ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data, 2019
Structured generative adversarial networks
Z Deng, H Zhang, X Liang, L Yang, S Xu, J Zhu, EP Xing
Advances in Neural Information Processing Systems, 2017
Black-box Detection of Backdoor Attacks with Limited Information and Data
Y Dong, X Yang, Z Deng, T Pang, Z Xiao, H Su, J Zhu
ICCV 2021, 2021
Exploring memorization in adversarial training
Y Dong, K Xu, X Yang, T Pang, Z Deng, H Su, J Zhu
ICLR 2022, 2022
LiBRe: A Practical Bayesian Approach to Adversarial Detection
Z Deng, X Yang, S Xu, H Su, J Zhu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021, 2021
Cavs: An efficient runtime system for dynamic neural networks
S Xu, H Zhang, G Neubig, W Dai, JK Kim, Z Deng, Q Ho, G Yang, EP Xing
2018 {USENIX} Annual Technical Conference ({USENIX}{ATC} 18), 937-950, 2018
Autosync: Learning to synchronize for data-parallel distributed deep learning
H Zhang, Y Li, Z Deng, X Liang, L Carin, E Xing
Advances in Neural Information Processing Systems 33, 906-917, 2020
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Z Deng, J Shi, J Zhu
International Conference on Machine Learning (ICML) 162, https://proceedings …, 2022
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning
Z Deng, J Zhu
14th Asian Conference on Machine Learning (ACML 2022), 2022
Neural Eigenfunctions Are Structured Representation Learners
Z Deng, J Shi, H Zhang, P Cui, C Lu, J Zhu
arXiv preprint arXiv:2210.12637, 2022
Measuring uncertainty through bayesian learning of deep neural network structure
Z Deng, Y Luo, J Zhu
2nd Workshop on Neural Architecture Search at ICLR 2021, 2021
Understanding and exploring the network with stochastic architectures
Z Deng, Y Dong, S Zhang, J Zhu
Advances in Neural Information Processing Systems 33, 14903-14914, 2020
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Z Deng, F Zhou, J Zhu
Advances in Neural Information Processing Systems, 2022
Accurate and reliable forecasting using stochastic differential equations
P Cui, Z Deng, W Hu, J Zhu
arXiv preprint arXiv:2103.15041, 2021
On Calibrating Diffusion Probabilistic Models
T Pang, C Lu, C Du, M Lin, S Yan, Z Deng
arXiv preprint arXiv:2302.10688, 2023
Deep Ensemble as a Gaussian Process Approximate Posterior
Z Deng, F Zhou, J Chen, G Wu, J Zhu
arXiv preprint arXiv:2205.00163, 2022
Confidence-based Reliable Learning under Dual Noises
P Cui, Y Yue, Z Deng, J Zhu
Advances in Neural Information Processing Systems, 2022
Efficient Inference for Dynamic Flexible Interactions of Neural Populations
F Zhou, Q Kong, Z Deng, J Kan, Y Zhang, C Feng, J Zhu
Journal of Machine Learning Research 23 (211), 1-49, 2022
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