AlphaGalileo

AdapGNN: A New Framework Enhances Explainability of Graph Neural Networks for Molecular Property Prediction

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...
EurekAlert!

Promising solution for detecting money-laundering and collusion in transaction webs

A review by researchers at Tongji University and the University of Technology Sydney highlights the powerful role of Graph Neural Networks (GNNs) in exposing financial fraud. By revealing intricate ...
AlphaGalileo

Graph learning and LLMs advance social network alignment research

With the growing use of multiple social platforms, aligning user identities across networks, known as Social Network Alignment (SNA), has become ...

Cochlea network model reveals how inner ear may sort sound from noise

Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...
Wired

Liquid AI Is Redesigning the Neural Network

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...
technologynetworks

Multiomics Data Integration With Machine Learning: Methods, Tools, and Biological Applications

Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...
Technology Networks

Deep Learning for Variant Calling: How DeepVariant and Neural Networks Are Improving Genomic Accuracy

Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...