DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...

Main outcome measures Cumulative time dependent intake of preservatives, including those in industrial food brands, assessed ...

Abstract: This study introduces Starformer, a hybrid model combining Graph Neural Networks (GNNs) with a novel Series-Core Fusion (SC-Fusion) mechanism for urban traffic prediction. By leveraging GNNs ...

Abstract: Graph Neural Network (GNN) has been widely applied in multivariate time series forecasting due to its excellent relationship modeling capabilities. However, current methods still face ...

If you're struggling with math, these best math AI tools can help you solve those complex problems and equations with ease.

TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...

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 ...

A breakthrough deal to attempt to limit global temperature rises was agreed at a conference of world nations in December 2015. These charts from the time show how and why the Earth’s climate is ...

Golden Software, a developer of mapping, plotting, and visualization software, has enhanced the Template experience in its Grapher scientific graphing package with improved ease of use and an online ...

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 ...