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Found 3 papers, 1 papers with code
An investigation of pre-upsampling generative modelling and Generative Adversarial Networks in audio super resolution
Our paper compares the pre-upsampling AudioUNet to a new generative model that upsamples the signal before using deep learning to transform it into a more believable signal.
Graph Representation Learning on Tissue-Specific Multi-Omics
Overall, the combination of RNA-sequencing and gene methylation data leads to a link prediction accuracy of 71% on GGI networks.
Graph representation forecasting of patient's medical conditions: towards a digital twin
Objective: Modern medicine needs to shift from a wait and react, curative discipline to a preventative, interdisciplinary science aiming at providing personalised, systemic and precise treatment plans to patients.
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