Loss functions and constraints improve sea surface height prediction

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...

Scientists Create a “Periodic Table” for Artificial Intelligence

Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...
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 ...
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 ...
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 ...
GitHub

Multi-task Learning using Message Passing Graph Neural Network for Radar based Perception Functions

Radar is increasingly recognized as a crucial sensor for Advanced Driver Assistance Systems (ADAS) and autonomous driving (AD) perception tasks. Its ability to penetrate occlusions, withstand adverse ...
GitHub

Mathematics of Machine Learning

Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to ...