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6 days ago · And then, we propose a meta-path based graph neural network, namely GraphRecruit, to further learn both latent student and enterprise portrait representations.
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7 days ago · To address the inefficacy of the existing GNES model in improving the global explainability through global explanation supervision, in this study, we extend the ...
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7 days ago · 03:15 Real-time visualization of large networks and embeddings from scholarly datasets using Helios-Web #109. Filipi de Silva Nascimiento (Indiana University).
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6 days ago · In particular, we first propose a Multi-Graph Embedding (MGE) module to generate the multiple graph representations based on multiple topological graph ...
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6 days ago · This article reviews evidence for the following three propositions using extensive body of scientific research and related sources from the cognitive and ...
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7 days ago · Specifically, to exploit the graph-structured knowledge, we first construct the program dependence graph to extract control and data dependencies among modules.
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6 days ago · Specifically, this method is based on graph embedding and spectral regression approaches, where the exploitation of the between-class Laplacian matrix makes ...
4 days ago · Here, to enhance the CCS predictive performance for various chemical classes of small molecules, we developed a chemical class-based Multimodal Graph ATtention ...
5 days ago · Responding to the challenge, we propose a tabular data generation framework guided by downstream task optimization (TDGGD). It incorporates three indicators ...
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10 hours ago · Influence on Confidence Regions for Regression Coefficients in Generalized Linear Models (pp. ... network, by maximizing the likelihood after marginalizing ...