activity
20182023
most citedData-Free Adversarial Distillation

103 citations · 268 across the 12 of their papers we have counts for

collaborators

19 papers

cs.CV20223 cited

Attention Diversification for Domain Generalization

Rang Meng, Xianfeng Li, Weijie Chen +7

Convolutional neural networks (CNNs) have demonstrated gratifying results at learning discriminative features. However, when applied to unseen domains, state-of-the-art models are…

cs.LG2022

A Survey of Neural Trees

Haoling Li, Jie Song, Mengqi Xue +4

Neural networks (NNs) and decision trees (DTs) are both popular models of machine learning, yet coming with mutually exclusive advantages and limitations. To bring the best of the…

eess.SY2022

Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power System

Kaixuan Chen, Shunyu Liu, Na Yu +5

The real-time transient stability assessment (TSA) plays a critical role in the secure operation of the power system. Although the classic numerical integration method, \textit{i.e…

cs.CV202297 cited

Spot-adaptive Knowledge Distillation

Jie Song, Ying Chen, Jingwen Ye +1

Knowledge distillation (KD) has become a well established paradigm for compressing deep neural networks. The typical way of conducting knowledge distillation is to train the studen…

cs.CV2022

Meta-attention for ViT-backed Continual Learning

Mengqi Xue, Haofei Zhang, Jie Song +1

Continual learning is a longstanding research topic due to its crucial role in tackling continually arriving tasks. Up to now, the study of continual learning in computer vision is…

eess.IV20226 cited

Dual Perceptual Loss for Single Image Super-Resolution Using ESRGAN

Jie Song, Huawei Yi, Wenqian Xu +3

The proposal of perceptual loss solves the problem that per-pixel difference loss function causes the reconstructed image to be overly-smooth, which acquires a significant progress…