May 30, 2020 · Conditional generative adversarial networks train two models against each other while leveraging side information learn from a given dataset to ...
To address this challenge, we employed a deep learning framework to construct a data- driven simulation of microbiome data using a conditional generative ...
The idea behind a GAN is to use two competing networks: one to generate data coherent with the input dataset, and the other to try to detect whether that ...
Performance of Machine Learning in Microbiome Datasets - SciTePress
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Reiman, D. and Dai, Y. Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets.
May 21, 2020 · Conditional generative adversarial networks train two models against each other while leveraging side information learn from a given dataset to ...
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Posted: Aug 24, 2021
Posted: Aug 24, 2021
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Posted: Jan 13, 2021
Posted: Jan 13, 2021
Conditional generative adversarial networks train two models against each other while leveraging side information learn from a given dataset to compute larger ...
Apr 3, 2024 · We propose a deep learning framework phylaGAN to augment the existing datasets with generated microbiome data using a combination of conditional generative ...
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May 21, 2020 · Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets https://biorxiv.org ...