MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
本篇論文「MAD-GAN：利用GAN對時間序列數據進行多元異常檢測」，發表於2019ICANN上，文章主要圍繞」異常檢測+多元時間序列+網絡入侵+GAN「展開，以下是我這幾天閱讀該篇文章的收穫，其中，模型及結構我自己做了一個動畫版，動畫版我用了很久的時間去理順作者的思想做出來的，能夠更直觀明確地表現出該模型的流程，但是我還不太清楚怎麼怎麼將動畫展示在博客中，後期如果學會我會及時更新，如果有小夥伴着
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相關文章
- 1. 論文譯文《ANOMALY DETECTION WITH GENERATIVE ADVERSARIAL NETWORKS》
- 2. Time Series Anomaly Detection
- 3. Recurrent neural networks for multivariate time series with missing values文獻閱讀
- 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