Results 41 to 50 of about 649,217 (300)

Isometric embeddings of graphs [PDF]

Proceedings of the National Academy of Sciences, 1984
We prove that any finite undirected graph can be canonically embedded isometrically into a maximum cartesian product of irreducible factors.
Graham, R. L., Winkler, P. M.
openaire   +3 more sources

Text-Graph Enhanced Knowledge Graph Representation Learning

Frontiers in Artificial Intelligence, 2021
Knowledge Graphs (KGs) such as Freebase and YAGO have been widely adopted in a variety of NLP tasks. Representation learning of Knowledge Graphs (KGs) aims to map entities and relationships into a continuous low-dimensional vector space.
Linmei Hu, Mengmei Zhang, Shaohua Li, Jinghan Shi, Chuan Shi, Cheng Yang, Zhiyuan Liu   +6 more
doaj   +1 more source

Joint-Tree Model and the Maximum Genus of Graphs [PDF]

, 2012
In 1971, Nordhaus, Stewart and White introduced the idea of the maximum genus of graphs.Since then many researchers have paid attention to this object and obtained many interesting results.
Dong, Guanghua, Wang, Ning, Yuanqiu, Huang, Liu, Yanpei   +3 more
core   +1 more source

Jurian/graph-embeddings: Disembed

, 2022
Disembed release, no more R and c++ code.
Jurian Baas
core   +1 more source

Graph learning considering dynamic structure and random structure

Journal of King Saud University: Computer and Information Sciences, 2023
Graph data is an important data type for representing the relationships between individuals, and many research works are conducted based on graph data.
Haiyao Dong, Haoming Ma, Zhenguang Du, Zhicheng Zhou, Haitao Yang, Zhenyuan Wang   +5 more
doaj   +1 more source

Embeddings of graphs

Discrete Mathematics, 1994
The author surveys some recent results about graphs embedded on higher surfaces or in general topological spaces. He begins by examining the relationship between the Jordan Curve Theorem and Kuratowski's Theorem. In particular, he discusses his result that in an arbitrary arcwise connected Hausdorff space which is not a simple closed curve and in which
openaire   +2 more sources

DBpedia RDF2Vec Graph Embeddings

, 2022
DBpedia graph embeddings using RDF2Vec. RDF2Vec embedding generation code can be found here and is based on a publication by Portisch et al. [1].
Hose, Katja, Martin Pekár Christensen, Matteo Lissandrini, Lissandrini, Matteo, Katja Hose, Christensen, Martin Pekár   +5 more
core   +2 more sources

Ellipsoidal Embeddings of Graphs

SIAM Journal on Applied Mathematics
Due to their flexibility to represent almost any kind of relational data, graph-based models have enjoyed a tremendous success over the past decades. While graphs are inherently only combinatorial objects, however, many prominent analysis tools are based on the algebraic representation of graphs via matrices such as the graph Laplacian, or on ...
Michaël Fanuel, Antoine Aspeel, Michael T. Schaub, Jean-Charles Delvenne   +3 more
openaire   +6 more sources

Tensors and tensor decompositions for combining external information with knowledge graph embeddings [PDF]

, 2021
The task of knowledge graph (KG) completion, where one is given an incomplete KG as a list of facts, and is asked to give high scores to correct but unseen triples, has been a well-studied problem in the NLP community. A simple but surprisingly robust
Balkır, Esma
core   +1 more source

A Topical Review of Graph Embedding in Graph Neural Networks

IEEE Access
Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support tasks such as node classification, link prediction and community ...
Willian Borges De Lemos, Lucas De Angelo Martins Ribeiro, Vanessa Telles Da Silva, Alessandro De Lima Bicho, Marcelo De Gomensoro Malheiros, Marcelo Rita Pias   +5 more
doaj   +1 more source