Simon Fraser University

Calculating Principal Components

Principal component analysis summarizes high dimensional data into a few dimensions. Each dimension is called a principal component and represents a linear combination of the variables. The first ...
IEEE

MGCL: Multiorder Graph Neural Network With Cross-Learning for Multivariate Time-Series Anomaly Detection

Abstract: Multivariate time-series (MTS) anomaly detection is critical for industrial systems. However, for inter-variable dimensional modeling, existing work mainly focuses on low-order dependencies ...
IEEE

Imagery Speech Classification Based on General Successive Multivariate Variational Mode Decomposition With Different Objective Functions Having Different Weights

Abstract: The imagery speech (IS) is the speech that the human beings are thinking in their brain. A brain computer interface (BCI) system is employed to translate the speech thinking in the brain to ...
GitHub

Spatio-temporal Fusion Flow with Dynamic Graph Leaning for Unsupervised Multivariate Time Series Anomaly Detection

Detecting anomalies in multivariate time series (MTS) is essential for maintaining system safety in industrial environments. Due to the challenges associated with acquiring labeled data, unsupervised ...
GitHub

NVIDIA Context Aware RAG

Context Aware RAG is a flexible library designed to seamlessly integrate into existing data processing workflows to build customized data ingestion and retrieval (RAG) pipelines. With Context Aware ...