Tech Xplore

AI model predicts robberies across US cities with 86.3% accuracy

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...
Frontiers

scCCVGBen for benchmarking of single-cell representation learning anchored on a centroid-coupled variational graph attention autoencoder across scRNA-seq and scATAC-seq

Six additional scRNA-seq datasets are reserved for the biological case studies (Sections 3.8–3.10) and excluded from every benchmark statistic: sleep-deprivation bone marrow (GSE280145), a TPO-induced ...
IEEE

Empower Multiscale Masked Graph Autoencoder With Graph Structural Entropy

Abstract: Graph self-supervised learning (GSSL) has shown great promise in addressing the label scarcity problem in real-world graphs, yet existing generative self-supervised learning (SSL) methods ...
Time

6 Graphs That Show Where the U.S. Leads China on AI—and Where It Doesn’t

Follow this section to personalize your feed and get instant alerts. WHY FOLLOW? Update your preferences in Account Settings Personalized Content Follow this tag to personalize your feed and get ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
GitHub

GraphCSVAE: Graph Categorical Structured Variational Autoencoder for Spatiotemporal Auditing of Physical Vulnerability Towards Sustainable Post-Disaster Risk Reduction

A Local-Scale Dataset of Annual Spatiotemporal Maps of Physical Vulnerability in the Cyclone-Impacted Coastal Khurushkul Community (Bangladesh) and Mudslide-Affected Freetown (Sierra Leone) (2016–2023 ...
C&EN

Mathematical Modeling of Aβ-42 Dimerization Dynamics: Integrating Physics-Based Simulations, Graph-Based Variational Autoencoder-Driven Neural Relational Inference, and Chaos ...

Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahçeşehir University, Istanbul 34349, Turkey Lab for Innovative Drugs (Lab4IND), ...
Scientific Research Publishing

Jin, W., Barzilay, R. and Jaakkola, T. (2018) Junction Tree Variational Autoencoder for Molecular Graph Generation. International Conference on Machine Learning, Stockholm, 10 ...

ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...
GitHub

AEGAE: Attribute-Embedded Graph Autoencoder

This repository provides the implementation of the AEGAE method for community detection in attributed graphs. AEGAE integrates Laplacian regularization and a graph autoencoder to generate robust node ...