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Graph Clustering

22 papers with code · Graphs

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Variational Graph Auto-Encoders

21 Nov 2016tkipf/gae

We introduce the variational graph auto-encoder (VGAE), a framework for unsupervised learning on graph-structured data based on the variational auto-encoder (VAE).

GRAPH CLUSTERING LINK PREDICTION

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

KDD 2019 benedekrozemberczki/ClusterGCN

Furthermore, Cluster-GCN allows us to train much deeper GCN without much time and memory overhead, which leads to improved prediction accuracy---using a 5-layer Cluster-GCN, we achieve state-of-the-art test F1 score 99. 36 on the PPI dataset, while the previous best result was 98. 71 by [16].

 SOTA for Node Classification on Pubmed (F1 metric )

GRAPH CLUSTERING NODE CLASSIFICATION

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

KDD 2019 benedekrozemberczki/ClusterGCN

Furthermore, Cluster-GCN allows us to train much deeper GCN without much time and memory overhead, which leads to improved prediction accuracy---using a 5-layer Cluster-GCN, we achieve state-of-the-art test F1 score 99. 36 on the PPI dataset, while the previous best result was 98. 71 by [16].

GRAPH CLUSTERING LINK PREDICTION NODE CLASSIFICATION

Adversarially Regularized Graph Autoencoder for Graph Embedding

13 Feb 2018Ruiqi-Hu/ARGA

Graph embedding is an effective method to represent graph data in a low dimensional space for graph analytics.

GRAPH CLUSTERING GRAPH EMBEDDING LINK PREDICTION

Residual Gated Graph ConvNets

ICLR 2018 xbresson/spatial_graph_convnets

In this paper, we are interested to design neural networks for graphs with variable length in order to solve learning problems such as vertex classification, graph classification, graph regression, and graph generative tasks.

GRAPH CLASSIFICATION GRAPH CLUSTERING GRAPH REGRESSION

Learning Networks from Random Walk-Based Node Similarities

23 Jan 2018cnmusco/graph-similarity-learning

In this work we consider a privacy threat to a social network in which an attacker has access to a subset of random walk-based node similarities, such as effective resistances (i. e., commute times) or personalized PageRank scores.

ANOMALY DETECTION GRAPH CLUSTERING GRAPH SIMILARITY

Affinity Clustering: Hierarchical Clustering at Scale

NeurIPS 2017 MahsaDerakhshan/AffinityClustering

In particular, we propose affinity, a novel hierarchical clustering based on Boruvka's MST algorithm.

GRAPH CLUSTERING

Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction

20 Aug 2018nlpub/watset-java

We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of domains.

GRAPH CLUSTERING

Hierarchical Graph Clustering using Node Pair Sampling

5 Jun 2018tbonald/paris

We present a novel hierarchical graph clustering algorithm inspired by modularity-based clustering techniques.

GRAPH CLUSTERING

A Streaming Algorithm for Graph Clustering

9 Dec 2017ahollocou/graph-streaming

We introduce a novel algorithm to perform graph clustering in the edge streaming setting.

GRAPH CLUSTERING