IEEE

Generalizing Graph Neural Networks on Out-of-Distribution Graphs

Graph Neural Networks (GNNs) are proposed without considering the agnostic distribution shifts between training graphs and testing graphs, inducing the degeneration of the generalization ability of ...

One Basic Excel Formula Generates Auto-Updating Visual Dashboards

Discover how to replace traditional Excel chart objects with clean, customizable in-cell visualizations using a single ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

LeL-GNN: Learnable Edge Sampling and Line Based Graph Neural Network for Link Prediction

Abstract: Graph neural networks lose a lot of their computing power when more network layers are added. As a result, the majority of existing graph neural networks have a shallow depth of learning.
YouTube on MSN

I transformed my Excel with these visuals

Create five advanced Excel visuals to impress anyone! This video covers how to create: 1. A column chart with automatically ...
JournalofAccountancy

Using Excel to identify financial statement red flags

Q. I read the JofA article last month about performing horizontal, vertical, and trend analyses in Excel. How can Excel be used to organize these analyses and highlight possible red flags in a company ...
Nature

Fault-tolerance amplification in line graphs: a framework for resilient PMU placement in power networks

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...