Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...
生物通

基于加权t-SNE的高维数据特征评分可视化评估新方法

为解决高维数据特征评分缺乏可视化评估工具的难题，研究人员提出"加权t-SNE"创新方法，通过修改t-SNE算法将特征重要性融入二维投影，结合轮廓系数定量评估，实现九类特征评分算法的直观比较，为机器学习可解释性研究提供新工具。 在生物医学和商业数据 ...
insideHPC

Research Highlights: MIT Develops First Generative Model for Anomaly Detection that ...

Kalyan Veeramachaneni and his team at the MIT Data-to-AI (DAI) Lab have developed the first generative model, the AutoEncoder with Regression (AER) for time series anomaly detection, that combines ...
InfoQ

Fraud Detection Using Random Forest, Neural Autoencoder, and Isolation Forest Techniques

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
TechCrunch

Financial firms should leverage machine learning to make anomaly detection easier

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...