most citedWeakly Augmented Variational Autoencoder in Time Series Anomaly Detection

2 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2024★ 1 cited

LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation

Hanze Ding, Zhangkai Wu, Jiyan Zhang +2

Few-shot segmentation models excel in metal defect detection due to their rapid generalization ability to new classes and pixel-level segmentation, rendering them ideal for address…

cs.LG2024★ 2 cited

Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection

Zhangkai Wu, Longbing Cao, Qi Zhang +2

Due to their unsupervised training and uncertainty estimation, deep Variational Autoencoders (VAEs) have become powerful tools for reconstruction-based Time Series Anomaly Detectio…

cs.LG2023

CVAE: Gaussian Copula-based VAE Differing Disentangled from Coupled Representations with Contrastive Posterior

Zhangkai Wu, Longbing Cao

We present a self-supervised variational autoencoder (VAE) to jointly learn disentangled and dependent hidden factors and then enhance disentangled representation learning by a sel…