Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...
Sub-headline: HUST researchers systematize SNA methods, building an evolutionary taxonomy based on graph representation ...
Abstract: Accurate and real-time traffic forecasting plays an important role in the intelligent traffic system and is of great significance for urban traffic planning, traffic management, and traffic ...
Abstract: Graph convolutional networks (GCNs) have attracted considerable interest in skeleton-based action recognition. Existing GCN-based models have proposed methods to learn dynamic graph ...
2026/06/02: add fixes and troubleshooting notes for open GitHub issues: safe FPS indexing during test, corrected Hausdorff calculation, more robust CGAL evaluation compilation/P2F handling, HDF5 ...
Digestive system cancers, including hepatobiliary and gastrointestinal malignancies, remain a major global oncological burden ...
PyTorch version should be 0.3! For PyTorch0.4 or higher, the codes need to be modified. Now we have updated the code to >=Pytorch0.4. A new model named AAGCN is added, which can achieve better ...
Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
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