Results 11 to 20 of about 2,125,479 (331)

Neural Graph Collaborative Filtering [PDF]

open access: yesAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019
Learning vector representations (aka. embeddings) of users and items lies at the core of modern recommender systems. Ranging from early matrix factorization to recently emerged deep learning based methods, existing efforts typically obtain a user's (or ...
Xiang Wang   +4 more
semanticscholar   +1 more source

Leveraging human resources for outbreak analysis: lessons from an international collaboration to support the sub-Saharan African COVID-19 response

open access: yesBMC Public Health, 2022
Emerging infectious diseases are a growing threat in sub-Saharan African countries, but the human and technical capacity to quickly respond to outbreaks remains limited.
Sara Botero-Mesa   +47 more
doaj   +1 more source

Odd Harmonious Labeling of PnC4 and  PnD2(C4)

open access: yesIndonesian Journal of Combinatorics, 2021
A graph G with q edges is said to be odd harmonious if there exists an injection f:V(G) → ℤ2q so that the induced function f*:E(G)→ {1,3,...,2q-1} defined by f*(uv)=f(u)+f(v) is a bijection.Here we show that graphs constructed by edge comb product of ...
Sabrina Shena Sarasvati   +2 more
doaj   +1 more source

Graph WaveNet for Deep Spatial-Temporal Graph Modeling [PDF]

open access: yesInternational Joint Conference on Artificial Intelligence, 2019
Spatial-temporal graph modeling is an important task to analyze the spatial relations and temporal trends of components in a system. Existing approaches mostly capture the spatial dependency on a fixed graph structure, assuming that the underlying ...
Zonghan Wu   +4 more
semanticscholar   +1 more source

COVID-19 in Switzerland real-time epidemiological analyses powered by EpiGraphHub

open access: yesScientific Data, 2022
Here we present the design and results of an analytical pipeline for COVID-19 data for Switzerland. It is applied to openly available data from the beginning of the epidemic in 2020 to the present day (august 2022).
Flávio Codeço Coelho   +2 more
doaj   +1 more source

Heterogeneous Graph Attention Network [PDF]

open access: yesThe Web Conference, 2019
Graph neural network, as a powerful graph representation technique based on deep learning, has shown superior performance and attracted considerable research interest.
Xiao Wang   +6 more
semanticscholar   +1 more source

Smart contracts

open access: yesInternet Policy Review, 2021
A smart contract is code deployed in a blockchain environment, or the source code from which such code was compiled.
Primavera De Filippi   +2 more
doaj   +1 more source

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning [PDF]

open access: yesAAAI Conference on Artificial Intelligence, 2018
Many interesting problems in machine learning are being revisited with new deep learning tools. For graph-based semi-supervised learning, a recent important development is graph convolutional networks (GCNs), which nicely integrate local vertex ...
Qimai Li, Zhichao Han, Xiao-Ming Wu
semanticscholar   +1 more source

DIMENSI METRIK DARI GRAF HASIL IDENTIFIKASI

open access: yesJurnal Matematika UNAND, 2022
Pada paper ini dibahas mengenai dimensi metrik dari graf hasil identififikasi. Dimensi metrik dari sebuah graf G, dinotasikan dengan dim(G), adalah kardinalitas paling kecil dari setiap himpunan pembeda di G.
Kristiana Wijaya
doaj   +1 more source

SuperGlue: Learning Feature Matching With Graph Neural Networks [PDF]

open access: yesComputer Vision and Pattern Recognition, 2019
This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points.
Paul-Edouard Sarlin   +3 more
semanticscholar   +1 more source

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