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 ...
Frontiers

A radiomic model leveraging conventional and Hessian matrix-based radiomic features from DCE-MRI for predicting efficacy of neoadjuvant chemotherapy in patients with HER2-low ...

Purpose: This study aimed to develop a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NAC) in patients with Human Epidermal Growth Factor Receptor 2 (HER2)-low breast cancer, ...
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 ...
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 ...