Results 291 to 300 of about 2,536,304 (342)

Cross-residual knowledge graph learning for robust multi-trait gene-trait prioritization in rice. [PDF]

Front Plant Sci
Wang J, Cui X, Fu X, Mao J, Zhang Y, Shan F, Zhou Z, Xing S, Hu X.   +8 more
europepmc   +1 more source

A unified MAP-EM approach to stable Gaussian mixture clustering with priors, graphs, and split-merge adaptation for document clustering. [PDF]

Front Artif Intell
Subbarayan S, Grace GH.
europepmc   +1 more source

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LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020
Graph Convolution Network (GCN) has become new state-of-the-art for collaborative filtering. Nevertheless, the reasons of its effectiveness for recommendation are not well understood.
Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang   +5 more
semanticscholar   +1 more source

Graph Attention Networks

International Conference on Learning Representations, 2017
We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their ...
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio   +5 more
semanticscholar   +1 more source

Specifying Knowledge Graph with Data Graph, Information Graph, Knowledge Graph, and Wisdom Graph

International Journal of Software Innovation, 2018
Knowledge graphs have been widely adopted, in large part owing to their schema-less nature. It enables knowledge graphs to grow seamlessly and allows for new relationships and entities as needed. A knowledge graph is a graph constructed by representing each item, entity and user as nodes, and linking those nodes that interact with each other via edges.
Yucong Duan, Lixu Shao, Gongzhu Hu
openaire   +1 more source

Spectral graph theory

Zeta and 𝐿-functions in Number Theory and Combinatorics, 2019
Spectral graph theory is a vast and expanding area of combinatorics. We start these notes by introducing and motivating classical matrices associated with a graph, and then show how to derive combinatorial properties of a graph from the eigenvalues of ...
A. Hinge
semanticscholar   +1 more source

Graph Decomposition of Slim Graphs

Graphs and Combinatorics, 1999
Let \(H\) be a fixed graph. An \(H\)-decomposition of an input graph \(G\) is a partition of the edge set of \(G\) such that each part forms a subgraph isomorphic to \(H\). This problem is known to be NP-complete as soon as \(H\) has a component with at least three edges. (This was conjectured by Holyer, and proved independently by \textit{D. Dor} and \
Yair Caro, Raphael Yuster
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An algebra of graphs and graph rewriting

2005
In this paper we propose an axiomatization of ‘partially abstract graphs’, i.e., of suitable classes of monomorphisms in a category of graphs, which may be interpreted as graphs having both a concrete part and an abstract part (defined up to isomorphism). Morphisms between pa-graphs are pushout squares.
CORRADINI, ANDREA, MONTANARI, UGO GIOVANNI ERASMO   +1 more
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GRAPHED: A Graph Description Diagram for Graph Databases

2018
Within recent years, graph database systems have become very popular and deployed mainly in situations where the relationship between data is significant, such as in social networks. Although they do not require a particular schema design, a data model contributes to their consistency.
Gustavo Cordeiro Galvão Van Erven, Waldeyr Mendes Cordeiro da Silva, Rommel N. Carvalho, Maristela Holanda   +3 more
openaire   +2 more sources