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Variational AutoEncoder For Regression: Application to Brain Aging Analysis
While unsupervised variational autoencoders (VAE) have become a powerful tool in neuroimage analysis, their application to supervised learning is under-explored. We aim to close this gap by proposing a unified probabilistic model for learning the latent space of imaging data and performing supervise...
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| I publikationen: | Med Image Comput Comput Assist Interv |
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| Huvudupphovsmän: | , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2019
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7377006/ https://ncbi.nlm.nih.gov/pubmed/32705091 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-32245-8_91 |
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