34 datasets found

The dataset used in this paper is a stochastic block model random graph, with a few vertices deemed interesting a priori.

Synthetic graphons with different resolutions and structures

A synthetic Barabasi network comprising 30 nodes with a power of the preferential attachment of 1.2

D&D, PROTEINS, and COLLAB datasets for graph classification tasks

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).

The dataset used in this paper is a probabilistic logic programming dataset, which is a probabilistic version of the Genes dataset.

The dataset used in the paper is the U.S. airport network.

A dataset for vehicular networks

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.

A dataset for generative network models that exhibit predefined ambiguity in their mesoscale structure.

The dataset used in the paper is a Kuramoto network with homogeneous and heterogeneous natural frequencies.

The dataset used in the paper is a synthetic network generated under four network models: SBM, DCBM, RDPG, and latent space model.

The dataset used in the paper is a collection of real and synthetic networks for community detection evaluation.

The dataset used in the paper is a collection of real and synthetic networks for community detection evaluation.

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.

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...

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)

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...

The dataset used in the paper is a link prediction benchmark dataset (Cora, PubMed, Disease, Airport) with a Gromov θ-hyperbolicity value.

The dataset used in the paper is heterogeneous graphs, including ACM citation network and IMDB movie network.