32 datasets found

Synthetic Generation dataset contains synthetic graph generation tasks.

The TUDataset is a collection of benchmark datasets for learning with graphs. It contains 14 datasets, each with a different type of graph.

Graph pooling is an essential component of the architecture for many graph-level tasks, such as graph classification and graph generation.

Graph Neural Networks (GNNs) have become a popular approach for various applications, ranging from social network analysis to modeling chemical properties of molecules.

GraphEraser is a novel machine unlearning framework tailored to graph data. It proposes two novel graph partition algorithms and a learning-based aggregation method to improve...

The dataset is used to train and test the weak Latent Dynamics Model (wLDM) and its variant, the weak Graph Koopman Bilinear Form (wGKBF) model.

The CORD-19 dataset contains academic journal articles relating to a variety of coronaviruses and related viral infections, not only COVID-19, sourced from PubMed Central (PMC),...

The dataset is used to test the performance of Tangent Bundle Neural Networks on three tasks: denoising of a tangent vector field on the torus, reconstruction from partial...

ogbg-molhiv dataset is a graph classification dataset containing 41k molecules.

Zinc12K dataset is a subset of ZINC250k containing 12k molecules.

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

The MoleculeNet dataset is a collection of molecular property prediction tasks. It contains 17 datasets, each with a different type of molecular graph.

The dataset used for traffic forecasting and brain network analysis.

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...

Mutag dataset is a benchmark dataset for graph neural networks, containing 188 cancer and 67 non-cancer cells.

Revisiting link prediction: a data perspective.

Mole-BERT: Rethinking pre-training graph neural networks for molecules.

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