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Social network graphs, knowledge graphs, citation networks, molecular graphs for GNN, web link graphs
322 datasets
Kaggle hosts a dataset titled 'ROGII No Memory GNN Lowest Train Artifacts'. The dataset's content and creator are not specified in the provided metadata. The last update date and data volume are unknown.
ROGII Balanced GNN Last Epoch Artifacts is a dataset of model artifacts from Kaggle. The title suggests it contains saved state from the final training epoch of a Graph Neural Network. Kaggle is a platform for sharing data science projects and competitions.
ROGII Balanced GNN Artifacts is a dataset published on Kaggle. Its title suggests it contains artifacts related to Graph Neural Networks, likely for training or evaluation. The dataset's specific content, size, and provenance are not detailed in the available metadata.
A dataset of traffic sign images, likely sourced from Kaggle. The specific number of images, collection method, and time range are not provided in the available metadata. The dataset appears to be intended for machine learning tasks related to road sign recognition.
Over 44,000 posts and 12,000 submolts from the Moltbook agent social network are annotated with content categories and toxicity levels. The dataset was created by TrustAIRLab and last updated in February 2026. It likely provides a basis for studying interactions and content moderation within AI agent communities.
A collection of the directed following network of the Bluesky social platform and associated user-created starter packs from late October 2025. Starter packs are curated lists of 6 to 150 users, with anonymized identifiers for users, creators, and packs. It is intended for computational analysis of network structures and the influence of starter packs.
A dataset related to neural networks, published on Kaggle. The specific contents, scale, and creation details are unknown from the provided metadata. Users must download the dataset to verify its actual structure and suitability for their tasks.
Encompassing the Bluesky following network and starter pack network data from late October 2025. It includes anonymized user identifiers and starter pack information for computational network analysis.
A large-scale social network dataset contains anonymized following relationships and user-curated starter packs from the Bluesky platform in January and February 2025. It includes directed following links and starter pack metadata, such as creator and member lists, for computational network analysis. The dataset was created by Alyssa Smith and harvested by ICPSR.
A geospatial raster layer representing waterbodies as a resistance component for a coastal marten connectivity model. The data was developed from the USGS National Hydrography Dataset, specifically extracting LakePond, Reservoir, Estuary, and SwampMarsh features from Oregon and California. The layer was last updated on March 4, 2026, by the Department of the Interior.
A geospatial raster layer representing bays and estuaries along the Pacific Coast, developed as part of a landscape connectivity model for the coastal marten (Martes caurina humboldtensis). The dataset was created by the Department of the Interior to fill null values in a primary land cover model, assigning a resistance value of 20 to each pixel. It was last updated on March 4, 2026.
A dataset published on Kaggle, likely containing data for training or evaluating a Graph Neural Network (GNN) model related to polymers. The specific data content, size, and creation details are unknown from the provided metadata.
A set of final node embeddings for the OGBn-MAG graph, a heterogeneous academic network from the Open Graph Benchmark. The embeddings are likely derived from a fusion of node features and graph structure, intended for machine learning tasks. The dataset is hosted on Kaggle, but its specific creation method and scale are not detailed in the provided metadata.
Logbook records from the Coastal Netters Logbook Program, part of River Herring Restoration and Anadromous Fish Investigations Programs. The dataset covers waterbodies including GREAT BAY ESTUARY and HAMPTON HARBOR. It was collected by organization SCIOPS under Grant F-61R.
GNN Exp Code is a dataset from Kaggle focused on Graph Neural Networks. The platform tags indicate it likely contains experimental code and graph data for machine learning purposes. The dataset's specific content, size, and authorship are not detailed in the provided metadata.
Ogbomoso, Nigeria, is the focal region for this dataset. It likely contains information related to the marketing of cashew nuts, such as prices, volumes, or market transactions. The dataset is published on Kaggle, but its specific contents, size, and creation details are unknown.
Data for IGSTGNN is a dataset hosted on Kaggle. The dataset's specific content, size, and structure are not described in the available metadata. Its intended use is likely for research or development related to graph neural networks, as suggested by its title.
OGBN-MAG is a heterogeneous academic graph from the Open Graph Benchmark. This dataset likely contains pre-computed node embeddings generated using the FUSE method after 200 training iterations. The embeddings were published on Kaggle, but the specific creation date and author are unknown.
fx_gnn data is a dataset hosted on Kaggle. The platform tags suggest it contains graph-structured data related to financial exchanges, likely intended for use with Graph Neural Networks. The author, organization, and specific details about the data's size, columns, and origin are unknown.
sna is a collection of tools for social network analysis authored by Carter T. Butts. The package includes methods for calculating node and graph-level indices, structural distance and covariance, detecting structural equivalence, performing network regression, generating random graphs, and visualizing networks in 2D and 3D. The dataset's size, specific file formats, and last update date are not provided.