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 ...
IEEE

DTFL: A Digital Twin-Assisted Graph Neural Network Approach for Service Function Chains Failure Localization

Abstract: Cloud computing enables Network Function Virtualization to dynamically provide and deploy network functions (NFs) to meet business-specific requirements. This approach streamlines NFs’ ...
Investopedia

Understanding Distribution Channels in Business: How They Function

Jason Fernando is a professional investor and writer who enjoys tackling and communicating complex business and financial problems. Natalya Yashina is a CPA, DASM with over 12 years of experience in ...
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 ...