82 datasets found

The dataset used in the paper is a graph neural network (GNN) dataset, where the goal is to learn a GNN with one hidden layer for node information convolution.

For autonomous vehicles (AVs), visual perception techniques based on sensors like cameras play crucial roles in information acquisition and processing. In various computer...

This paper introduces STAR, a framework for spatio-temporal crowd trajectory prediction with only attention mechanisms.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors evaluate CatFlow on a graph generation task.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors evaluate CatFlow on three sets of experiments: abstract graph generation,...

Reliable fault detection is an essential requirement for safe and efficient operation of complex mechanical systems in various industrial applications.

Open Graph Benchmark (OGB) dataset contains many large-scale benchmark datasets.

Benchmarking graph neural networks.

Graph Convolutional Networks (GCNs) with multi-hop aggregation is more expressive than one-hop GCN but suffers from higher model complexity. Finding the shortest aggregation...

The Coauthor Physics dataset is a co-authorship graph extracted from the Microsoft Academic Graph, with a focus on Physics research.

This dataset contains graph-structured data and its corresponding features.

Graph structure augmentation pipeline UniAug to leverage the increasing scale of graph data.

UniSG: A unified entity-component-system in a scenegraph architecture, designed to address the demands of scientific, visual, and neural computing applications.

UniSG^GA: A novel integrated scenegraph structure that incorporates behavior and geometry data on a 3D scene, designed to seamlessly integrate Graph Neural Networks (GNNs) and...

The proposed method learns latent interaction graph jointly with feature engineering and event identification model, thus improving the accuracy of the graph learning and...

OGB-MAG is a large-scale dataset used for node classification and link prediction.

DBLP, IMDB, ACM, and Freebase are four public datasets used for node classification and link prediction.

The complex spatial-temporal correlations in traffic data make the traffic forecasting problem challenging. The proposed model captures the time-varying spatial correlations by...

Graph Neural Networks (GNNs) are versatile, powerful machine learning methods that enable graph structure and feature representation learning, and have applications across many...

Multimodal Spatiotemporal Graph-Transformer for Hospital Readmission Prediction