Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost. It it ...

We identify four major challenges in graph deep learning: dynamic and evolving graphs, learning with edge signals and information, graph estimation, and the generalization of graph models. For each ...

At the 2025 World Intelligent Industry Expo, most car companies focused on showcasing and promoting new models. In contrast, ...

At the 2025 World Intelligent Industry Expo, most automotive companies focused on showcasing and promoting new models. In ...

Official implementation of Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation by Jun Hyeong Kim*, Seonghwan Kim*, Seokhyun Moon*, Hyeongwoo Kim*, Jeheon Woo*, Woo Youn Kim. [arXiv ...

AI is already rapidly redefining how we discover and design biologics, and as CTO at Cytiva, I’ve had the privilege of ...

This graph shows the rate of State reactions to the Director-General's requests for information on the judicial status of cases into journalist killings in % from 2013 to 2022. For more information on ...

Missense variants in the O-GlcNAc transferase ( OGT) gene have recently been shown to segregate with a syndromic form of intellectual disability (OGT-ID), underscoring the importance of protein ...

A GIS-Based Case Study on Char Kasem, Patuakhali, Bangladesh. Open Access Library Journal, 12, 1-20. doi: ...

Using interactive charts, see how mortgage rates have changed over time and impacted the housing market in modern history.