Tag: Graph Neural Networks

A new graph neural network framework makes skin lesion classification more transparent, but candid reporting reveals serious weaknesses in melanoma ...

A probabilistic dynamic graph deep learning model developed on Prince Edward Island predicted potato crop coefficients with R² values up ...

Researchers have built a graph neural network that classifies scientific papers by combining intuitionistic fuzzy uncertainty, node-level Laplacian energy, and ...

Zhejiang University researchers report a physics-guided framework combining generative imputation, dynamic graph attention, and a constrained decoder that achieved zero ...

A physics-informed graph neural network classified simulated collector-line cascading-trip risk with 0.972 accuracy and 0.91 recall for high-risk events in ...

A computational benchmarking study found that SubPoE delivered the strongest average spatial-domain clustering results across eight paired spatial multi-omics datasets ...

GraphLane combined three-frame context, uncertainty-weighted graph reasoning and road-geometry constraints to improve lane-coordinate estimates in a CULane study, although its ...

A supervised graph-learning model combining metapath embeddings, graph convolution and attention outperformed 12 baselines on the DBLP and ACM academic-network ...

A synthetic simulation of scan-to-order transactions found that DS-GNN ranked privacy-leakage paths and estimated risk more accurately than four baselines, ...

A retrospective study of 15,000 companies found that the MFGCN machine-learning framework outperformed tested baselines in two-quarter financial-crisis warning while ...