MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
本篇论文“MAD-GAN：利用GAN对时间序列数据进行多元异常检测”，发表于2019ICANN上，文章主要围绕”异常检测+多元时间序列+网络入侵+GAN“展开，以下是我这几天阅读该篇文章的收获，其中，模型及结构我自己做了一个动画版，动画版我用了很久的时间去理顺作者的思想做出来的，能够更直观明确地表现出该模型的流程，但是我还不太清楚怎么怎么将动画展示在博客中，后期如果学会我会及时更新，如果有小伙伴着
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相关文章
- 1. 论文译文《ANOMALY DETECTION WITH GENERATIVE ADVERSARIAL NETWORKS》
- 2. Time Series Anomaly Detection
- 3. Recurrent neural networks for multivariate time series with missing values文献阅读
- 4. Anomaly Detection for Business Metrics with R
- 5. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
- 6. （九）Anomaly Detection Based on Convolutional Recurrent Autoencoder for IoT Time Series
- 7. CartoonGAN: Generative Adversarial Networks for Photo Cartoonization
- 8. How to Use Convolutional Neural Networks for Time Series Classification
- 9. Generative Adversarial Networks for Hyperspectral Image Classification
- 10. （十）Unsupervised Anomaly Detection in Energy Time Series Data using Variational Recurrent Autoencoder