Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
This project provides an unsupervised learning solution for detecting anomalies in time-series data, specifically demonstrated on synthetic network traffic. It leverages a Long Short-Term Memory (LSTM ...
🎬 Supports video generation up to 2160×3840 resolution on a single H100 GPU ⚡ Delivers 14.8× faster inference than the base model 💰 230× lower training cost compared to training from scratch (only ...
Abstract: Hyperspectral unmixing is significant for advancing remote sensing (RS) applications, aiming at extracting the spectra of pure materials (called endmembers) and obtaining their proportions ...
Abstract: With the rapid growth of electric vehicle (EV) adoption, ensuring the reliability and safety of their battery systems is of significant importance. Current anomaly detection methods, which ...
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