IEEE

Counterfactual Data Augmentation With Denoising Diffusion for Graph Anomaly Detection

Abstract: A critical aspect of graph neural networks (GNNs) is to enhance the node representations by aggregating node neighborhood information. However, when detecting anomalies, the representations ...
University of Wyoming

Dice Roll Bar Graph

This module uses random number generators to simulate dice rolls. The user can provide any number of different sided dice and the number of times the dice are rolled. The program will then produce a ...
IEEE

Synchronous Spatiotemporal Graph Transformer: A New Framework for Traffic Data Prediction

Abstract: Modeling the spatiotemporal relationship (STR) of traffic data is important yet challenging for existing graph networks. These methods usually capture features separately in temporal and ...
GitHub

Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network

The inference of cell-cell communication (CCC) is crucial for a better understanding of complex cellular behavior and regulatory mechanisms in biological systems. However, current computational ...
BMJ

Effect of different visual presentations on the public’s comprehension of prognostic information using acute and chronic condition scenarios: two online randomised controlled ...

Objectives To assess the effectiveness of bar graph, pictograph and line graph compared with text-only, and to each other, for communicating prognosis to the public. Design Two online four-arm ...
news.bloomberglaw

TransUnion Sued Over July Data Breach Affecting 4 Million People

TransUnion LLC is facing a proposed class action accusing the credit reporting company of failing to protect the personally identifiable information of more than 4 million people that was exposed in a ...