BIOENGINEER

Graph neural network improves phase prediction in SAT solvers

Researchers report that a multi-scale graph neural network called NeuroMGCN improves SAT phase prediction and raises solving rates by 4.1 and 5.2 percent over Kissat in the SATCOMP-2023 and ...
BIOENGINEER

Fuzzy Graph Neural Network Sorts Research Papers Using Uncertainty and Trust

Researchers have built a graph neural network that classifies scientific papers by combining intuitionistic fuzzy uncertainty ...
Nature

Dynamic Graph Representation and Link Prediction Techniques

Dynamic graph representation serves as a framework for modelling systems whose structure evolves over time, incorporating changes in nodes and edges to capture temporal patterns. Link prediction ...
techtarget

What are graph neural networks (GNNs)?

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...
english.cas

Dynamic Clustering Accelerates Neural Networks on Resource-Constrained Platforms

Called Dynamic Clustering for Channel Pruning (DCCP), the method reduced the floating-point operations of ResNet-50 by 68.52% ...