123 citations · 470 across the 19 of their papers we have counts for
10 papers · 1 filter
Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting
Mengzhang Li, Zhanxing Zhu
Spatial-temporal data forecasting of traffic flow is a challenging task because of complicated spatial dependencies and dynamical trends of temporal pattern between different roads…
Amata: An Annealing Mechanism for Adversarial Training Acceleration
Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou +1
Despite the empirical success in various domains, it has been revealed that deep neural networks are vulnerable to maliciously perturbed input data that much degrade their performa…
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
Guangda Ji, Zhanxing Zhu
Knowledge distillation is a strategy of training a student network with guide of the soft output from a teacher network. It has been a successful method of model compression and kn…
Automatic Data Augmentation for 3D Medical Image Segmentation
Ju Xu, Mengzhang Li, Zhanxing Zhu
Data augmentation is an effective and universal technique for improving generalization performance of deep neural networks. It could enrich diversity of training samples that is es…
Neural Approximate Sufficient Statistics for Implicit Models
Yanzhi Chen, Dinghuai Zhang, Michael Gutmann +2
We consider the fundamental problem of how to automatically construct summary statistics for implicit generative models where the evaluation of the likelihood function is intractab…
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai +3
Convolutional Neural Networks (CNNs) are known to rely more on local texture rather than global shape when making decisions. Recent work also indicates a close relationship between…