Learning Network Representations
3 papers with code • 0 benchmarks • 0 datasets
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Most implemented papers
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks
chengw07/NetWalk
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ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2018
In this paper, we propose a novel approach, NetWalk, for anomaly detection in dynamic networks by learning network representations which can be updated dynamically as the network evolves.
Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis
noetits/ICE-Talk
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The field of Text-to-Speech has experienced huge improvements last years benefiting from deep learning techniques.
MFNets: Data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources
We present an approach for constructing a surrogate from ensembles of information sources of varying cost and accuracy.
