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, ...
HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
IEEE

DAHBM-GCN: A Flexible Graph Convolution Network Accelerator With Multiple Dataflows and HBM

Abstract: Graph-structured data has been widely applied in transportation, molecular, and e-commerce networks, etc. Graph Convolutional Network (GCN) has emerged as an efficient approach to processing ...
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 ...
IEEE

Modeling Relational Logic Circuits for And-Inverter Graph Convolutional Network

Abstract: The automation of logic circuit design enhances chip performance, energy efficiency, and reliability, and is widely applied in the field of Electronic Design Automation (EDA). And-Inverter ...
AlphaGalileo

Crossing Virtual Boundaries: Rethinking Social Network Alignment via Graph Learning

Sub-headline: HUST researchers systematize SNA methods, building an evolutionary taxonomy based on graph representation ...