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Stochastic Block Model Random Graph
The dataset used in this paper is a stochastic block model random graph, with a few vertices deemed interesting a priori. -
Synthetic graphons
Synthetic graphons with different resolutions and structures -
Synthetic Barabasi network
A synthetic Barabasi network comprising 30 nodes with a power of the preferential attachment of 1.2 -
D&D, PROTEINS, and COLLAB datasets
D&D, PROTEINS, and COLLAB datasets for graph classification tasks -
Barabasi-Albert Graphs
The dataset used in this paper is a collection of Barabasi-Albert (BA) graphs with different preferential attachment factors (m) ranging from m = 1 (BA-1) to m = 6 (BA-6). -
U.S. Airport Network
The dataset used in the paper is the U.S. airport network. -
Vehicular Networks dataset
A dataset for vehicular networks -
Matrix-weighted network with n agents and d-dimensional weights
The dataset used in this paper is a matrix-weighted network with n agents, each of dimension d. The network is structurally imbalanced and has a unique non-trivial balancing set. -
Stochastic Cross-Block Model
A dataset for generative network models that exhibit predefined ambiguity in their mesoscale structure. -
Kuramoto Network Datasets
The dataset used in the paper is a Kuramoto network with homogeneous and heterogeneous natural frequencies. -
Synthetic Networks
The dataset used in the paper is a synthetic network generated under four network models: SBM, DCBM, RDPG, and latent space model. -
Scientific Collaboration Networks
The dataset used in the paper is a collection of real and synthetic networks for community detection evaluation. -
Community Detection Evaluation
The dataset used in the paper is a collection of real and synthetic networks for community detection evaluation. -
Graph Datasets
The dataset used in this paper is a collection of real-world graph datasets from various domains, including biological networks, social networks, and collaboration networks. -
Protein Interaction Network
The dataset used in the paper is a protein interaction network with 82 nodes, where each node has a classification of one of 6 experimental modifications observed from the... -
Microbiome Subject Similarity Network
The dataset used in the paper is a microbiome subject similarity network with 121 nodes, where each node has a 130-dimensional vector of attributes (counts) -
Synthetic Network
The dataset used in the paper is a synthetic network with 200 nodes and 4 communities, parameterized as follows: p(Aij = 1) ∼ Bernoulli(.10), Bernoulli(.25), if zi (cid:54)= zj... -
ACM citation network and IMDB movie network
The dataset used in the paper is heterogeneous graphs, including ACM citation network and IMDB movie network.
