在工业质检、安全监控等领域， 多类别无监督异常检测（Multi-class Unsupervised Anomaly Detection, MUAD） 一直是个极具挑战的课题。传统的做法通常是训练一个复杂的编码器-解码器模型，试图重建正常样本的特征。但你有没有想过，这种费时费力的“训练”过程，真的是必须的吗？

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...

Artificial intelligence is reshaping cybersecurity, but much of that progress has focused on cloud and enterprise ...

The funding backs continued innovation in production-grade forecasting, anomaly detection, and artificial intelligence.

Discover how to secure AI orchestration workflows using post-quantum cryptography and AI-driven anomaly detection for Model Context Protocol (MCP) environments.

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

In today’s digital world, fraud has become more complex, which means we need smarter ways to detect and prevent it. Generative AI helps with this by looking at large amounts of data in real-time, ...

Black Book outlines an AI-era integrity architecture for healthcare benchmarking, instrumentation hardening, tiered ...