Showing results 1 to 20 of 25
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| Issue Date | Title | Author(s) |
| 1-Oct-2022 | Adaptive Progressive Continual Learning | Xu, Ju; Ma, Jin; Gao, Xuesong; Zhu, Zhanxing |
| 21-Mar-2020 | Adversarial attacks on Faster R-CNN object detector | Wang, Yutong; Wang, Kunfeng; Zhu, Zhanxing; Wang, Fei-Yue |
| 2021 | Adversarial Invariant Learning | Ye, Nanyang; Tang, Jingxuan; Deng, Huayu; Zhou, Xiao-Yun; Li, Qianxiao; Li, Zhenguo; Yang, Guang-Zhong; Zhu, Zhanxing |
| 2021 | Amata: An Annealing Mechanism for Adversarial Training Acceleration | Ye, Nanyang; Li, Qianxiao; Zhou, Xiao-Yun; Zhu, Zhanxing |
| 2018 | Bayesian Adversarial Learning | Ye, Nanyang; Zhu, Zhanxing |
| 2023 | Differential effect of interventions in patients with prediabetes stratified by a machine learning-based diabetes progression prediction model | Zou, Xiantong; Luo, Yingying; Huang, Qi; Zhu, Zhanxing; Li, Yufeng; Zhang, Xiuying; Zhou, Xianghai; Ji, Linong |
| 2020 | Efficient Neural Architecture Search via Proximal Iterations | Yao, Quanming; Xu, Ju; Tu, Wei-Wei; Zhu, Zhanxing |
| Dec-2022 | GrOD: Deep Learning with Gradients Orthogonal Decomposition for Knowledge Transfer, Distillation, and Adversarial Training | Xiong, Haoyi; Wan, Ruosi; Zhao, Jian; Chen, Zeyu; Li, Xingjian; Zhu, Zhanxing; Huan, Jun |
| 2020 | Learning to Search Efficient DenseNet with Layer-wise Pruning | Zhang, Xuanyang; Liu, Hao; Zhu, Zhanxing; Xu, Zenglin |
| 2020 | Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes | Sun, Ke; Lin, Zhouchen; Zhu, Zhanxing |
| 2019 | Novel subgroups of patients with adult-onset diabetes in Chinese and US populations | Zou, Xiantong; Zhou, Xianghai; Zhu, Zhanxing; Ji, Linong |
| 2020 | On Breaking Deep Generative Model-based Defenses and Beyond | Chen, Yanzhi; Xie, Renjie; Zhu, Zhanxing |
| 2018 | Reinforced Continual Learning | Xu, Ju; Zhu, Zhanxing |
| Apr-2021 | Sampling Sparse Representations with Randomized Measurement Langevin Dynamics | Wang, Kafeng; Xiong, Haoyi; Bian, Jiang; Zhu, Zhanxing; Gao, Qian; Guo, Zhishan; Xu, Cheng-Zhong; Huan, Jun; Dou, Dejing |
| 2020 | Simplifying Graph Attention Networks with Source-Target Separation | Guo, Hantao; Yan, Rui; Feng, Yansong; Gao, Xuesong; Zhu, Zhanxing |
| 2018 | SIPID: A deep learning framework for sinogram interpolation and image denoising in low-dose CT reconstruction | Yuan, Huizhuo; Jia, Jinzhu; Zhu, Zhanxing |
| 2021 | Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting | Li, Mengzhang; Zhu, Zhanxing |
| 2018 | Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting | Yu, Bing; Yin, Haoteng; Zhu, Zhanxing |
| 1-Jan-2021 | Spatio-Temporal Manifold Learning for Human Motions via Long-Horizon Modeling | Wang, He; Ho, Edmond S. L.; Shum, Hubert P. H.; Zhu, Zhanxing |
| 2019 | SpHMC: Spectral Hamiltonian Monte Carlo | Xiong, Haoyi; Wang, Kafeng; Bian, Jiang; Zhu, Zhanxing; Xu, Cheng-Zhong; Guo, Zhishan; Huan, Jun |
