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Graph Matching

26 papers with code · Graphs

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graph2vec: Learning Distributed Representations of Graphs

17 Jul 2017benedekrozemberczki/karateclub

Recent works on representation learning for graph structured data predominantly focus on learning distributed representations of graph substructures such as nodes and subgraphs.

GRAPH CLASSIFICATION GRAPH EMBEDDING GRAPH MATCHING

Learning Combinatorial Embedding Networks for Deep Graph Matching

ICCV 2019 Thinklab-SJTU/PCA-GM

In addition with its NP-completeness nature, another important challenge is effective modeling of the node-wise and structure-wise affinity across graphs and the resulting objective, to guide the matching procedure effectively finding the true matching against noises.

GRAPH EMBEDDING GRAPH MATCHING

The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development

22 May 2019HDI-Project/BTB

To address these problems, we introduce the Machine Learning Bazaar, a new framework for developing machine learning and automated machine learning software systems.

ANOMALY DETECTION AUTOML GRAPH MATCHING

MolGAN: An implicit generative model for small molecular graphs

30 May 2018nicola-decao/MolGAN

Deep generative models for graph-structured data offer a new angle on the problem of chemical synthesis: by optimizing differentiable models that directly generate molecular graphs, it is possible to side-step expensive search procedures in the discrete and vast space of chemical structures.

GRAPH MATCHING

Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers

25 Mar 2020martius-lab/blackbox-backprop

Building on recent progress at the intersection of combinatorial optimization and deep learning, we propose an end-to-end trainable architecture for deep graph matching that contains unmodified combinatorial solvers.

COMBINATORIAL OPTIMIZATION GRAPH MATCHING

SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences

CVPR 2019 intellhave/SDRSAC

In particular, our work enables the use of randomized methods for point cloud registration without the need of putative correspondences.

GRAPH MATCHING POINT CLOUD REGISTRATION

SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences

6 Apr 2019intellhave/SDRSAC

In particular, our work enables the use of randomized methods for point cloud registration without the need of putative correspondences.

GRAPH MATCHING POINT CLOUD REGISTRATION

Deep Graph Matching Consensus

ICLR 2020 rusty1s/deep-graph-matching-consensus

This work presents a two-stage neural architecture for learning and refining structural correspondences between graphs.

 SOTA for Entity Alignment on DBP15k zh-en (using extra training data)

ENTITY ALIGNMENT GRAPH MATCHING KNOWLEDGE GRAPHS

Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

ACL 2019 nju-websoft/JAPE

Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs.

ENTITY EMBEDDINGS GRAPH MATCHING

Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection

22 Aug 2017xiaojunxu/dnn-binary-code-similarity

The problem of cross-platform binary code similarity detection aims at detecting whether two binary functions coming from different platforms are similar or not.

GRAPH EMBEDDING GRAPH MATCHING MALWARE DETECTION