Results 21 to 30 of about 4,550,446 (348)
On the enumeration of uniquely reducible double designs [PDF]
A double $2$-$(v,k,2 \lambda)$ design is a design which is reducible into two $2$-$(v,k,\lambda)$ designs. It is called uniquely reducible if it has, up to equivalence, only one reduction.
Veerle Fack +2 more
doaj +1 more source
Graph Convolutional Neural Networks for Web-Scale Recommender Systems [PDF]
Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods practical and scalable to web-scale recommendation tasks with billions of items
Rex Ying +5 more
semanticscholar +1 more source
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 Pn ⊵ C4 and Pn ⊵ D2(C4)
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]
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
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
SuperGlue: Learning Feature Matching With Graph Neural Networks [PDF]
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
Heterogeneous Graph Attention Network [PDF]
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
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]
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

