While every college admissions department evaluates applicants a bit differently, standardized test scores are a big piece of ...

Background Preterm birth is associated with lifelong respiratory sequelae, yet our understanding of lung function ...

A dispute over how to divvy up the pot in an interrupted game of chance led early mathematicians to invent modern risk ...

Recently, a cheerful 100-year-old message in a bottle was found on the south-west coast of Australia. In it, a world war one ...

Here's the revised description with all links and additional text removed: Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set ...

GOOD (Graph OOD) is a graph out-of-distribution (OOD) algorithm benchmarking library depending on PyTorch and PyG to make develop and benchmark OOD algorithms easily. Currently, GOOD contains 11 ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

This paper explores the applications of Fusion Graph Neural Network (FuGNN) on power distribution systems. FuGNN effectively models dynamic networks with evolving topology and features. Applied to ...

Interest Rate Probability Distributions Implied by Derivatives Prices is a daily measure of the distribution of future short-term interest rates, calculated from prices of fixed-income derivatives ...

State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry College of Chemistry and Chemical Engineering, Xiamen ...

Abstract: R-convolution graph kernels are conventional methods for graph classification. They decompose graphs into substructures and aggregate all the substructure similarity as graph similarity.