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Graph Similarity

16 papers with code · Graphs

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DDGK: Learning Graph Representations for Deep Divergence Graph Kernels

21 Apr 2019google-research/google-research

Second, for each pair of graphs, we train a cross-graph attention network which uses the node representations of an anchor graph to reconstruct another graph.

FEATURE ENGINEERING GRAPH CLASSIFICATION GRAPH SIMILARITY

Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

7 Mar 2017sk1712/gcn_metric_learning

Evaluating similarity between graphs is of major importance in several computer vision and pattern recognition problems, where graph representations are often used to model objects or interactions between elements.

GRAPH SIMILARITY METRIC LEARNING

Label Efficient Semi-Supervised Learning via Graph Filtering

CVPR 2019 liqimai/Efficient-SSL

However, existing graph-based methods either are limited in their ability to jointly model graph structures and data features, such as the classical label propagation methods, or require a considerable amount of labeled data for training and validation due to high model complexity, such as the recent neural-network-based methods.

GRAPH SIMILARITY

SimGNN: A Neural Network Approach to Fast Graph Similarity Computation

WSDM '19 Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining 2019 yunshengb/SimGNN

Our model achieves better generalization on unseen graphs, and in the worst case runs in quadratic time with respect to the number of nodes in two graphs.

GRAPH CLASSIFICATION GRAPH SIMILARITY

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

Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity

1 Apr 2019yunshengb/UGraphEmb

We introduce a novel approach to graph-level representation learning, which is to embed an entire graph into a vector space where the embeddings of two graphs preserve their graph-graph proximity.

GRAPH CLASSIFICATION GRAPH EMBEDDING GRAPH SIMILARITY

Message Passing Graph Kernels

7 Aug 2018giannisnik/message_passing_graph_kernels

The first component is a kernel between vertices, while the second component is a kernel between graphs.

GRAPH SIMILARITY