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Social network graphs, knowledge graphs, citation networks, molecular graphs for GNN, web link graphs
322 datasets
Multi-factor economic indicators are provided for risk and connectivity modeling. The dataset is sourced from Kaggle and is associated with data analytics and cleaning tasks. Specific details on volume, authorship, and temporal coverage are unavailable.
A collection of a large-scale collection of residential floor plans structured as vector-graphs. The data captures architectural layouts and spatial connectivity to facilitate graph-based computational design and structural analysis.
MetaCogBench-tasks is a dataset hosted on Kaggle. The title suggests it contains a collection of tasks designed for benchmarking cognitive or metacognitive capabilities, likely in AI or psychology contexts. No further metadata is available to confirm its specific contents, size, or origin.
KG20C is a benchmark dataset for scholarly knowledge graphs, published on Kaggle. The dataset likely contains structured relationships between academic entities such as papers, authors, and institutions. Its exact size, creation date, and authorship are unknown.
1,000,000,000 network event records categorized into normal traffic and three specific attack types: DDoS, SQL injection (SQLi), and BruteForce. The dataset includes a pre-trained CatBoost model achieving 99.9% detection accuracy across these security event classes.
CAGNN Sum v6 Checkpoints are pre-trained model weights published on Kaggle. The dataset's specific architecture, training data, and performance metrics are not detailed in the provided metadata. Users must download the checkpoints to verify their intended application and compatibility.
A collection of tabular data describing the nodes and edges of causal networks derived from participatory modeling with local actors. It covers 26 territorial units across six intervention areas of the PACTE project, elucidating cause-and-effect relationships between policy, environmental, socioeconomic dynamics, and livelihood strategies.
CAGNN Sum v6 checkpoints are a set of pre-trained model weights for a Graph Neural Network, likely for graph classification or node representation tasks. The dataset is hosted on Kaggle and is tagged as a 'Pre Trained Model'. Specific details on the architecture, training data, and performance are not provided in the metadata.
Social network advertising data, likely containing user demographics and ad interaction metrics. The dataset is hosted on Kaggle, but its specific origin, size, and creation details are not provided in the available metadata. Further details about the columns, sample data, and license require verification after download.
Kaggle hosts this dataset, which likely contains information related to advertising on social media platforms. The specific variables, data collection method, and creator are not detailed in the available metadata. Its content and scale require verification after download.
A dataset likely containing graph-structured data for training or benchmarking Graph Neural Networks (GNNs). It is hosted on Kaggle, but the specific content, size, and creator are unknown. The dataset's last update date is also unknown.
CAGNN Sum Checkpoints likely contain saved model states for a Graph Neural Network architecture. The dataset is hosted on Kaggle and is tagged as a 'Pre Trained Model'. Specific details on the model's architecture, training data, and performance are not provided in the available metadata.
A dataset for training and evaluating Graph Neural Network (GNN) models, published on Kaggle. The specific content, scale, and origin are not detailed in the available metadata. Users must download the dataset to verify its structure, features, and intended applications.
An identity graph dataset published on Kaggle by Hamed Behrouzi. The dataset likely contains nodes and edges representing entities and their relationships, potentially for linking user identities across platforms. Specific details on size, time range, and collection method are not provided in the metadata.
A dataset of graphs likely enriched with features for training and evaluating Temporal Graph Neural Networks (TGNNs). The dataset is hosted on Kaggle, but its specific size, origin, and creation date are not provided in the available metadata. The title suggests the graphs are processed or augmented to support advanced graph learning tasks.
CAGNN Sum Checkpoints Wajahatb v1 is a dataset of pre-trained model checkpoints published on Kaggle. The title suggests it relates to a Graph Neural Network (GNN) architecture named CAGNN. The dataset likely contains saved model states for tasks involving graph-structured data.
CAGNN Sum v6 Checkpoints are pre-trained model files hosted on Kaggle. The title suggests the data relates to a Graph Neural Network architecture, likely for tasks involving graph-structured data. Metadata is minimal; actual content and performance require verification after download.
A graph dataset representing connections between artist pages on the Facebook social media platform. The dataset's exact size, creator, and creation date are not specified in the provided metadata. It was sourced from Kaggle, a platform for sharing datasets.
CAGNN Sum Checkpoints Wajahatb is a collection of pre-trained model checkpoints for a Graph Neural Network (GNN) architecture, likely the Context-Aware Graph Neural Network (CAGNN). The dataset contains saved model states from the Kaggle user 'Wajahatb', intended for tasks involving a 'sum' operation on graph-structured data. Specific details on the number of checkpoints, training data, and creation date are unavailable.
Harvard Dataverse hosts a dataset by YUHAO WANG analyzing spatial-institutional misfit within China's Marine Protected Area network. The dataset supports research in Social Sciences and Earth and Environmental Sciences, though specific row and column counts are not provided. It was last updated in January 2026.