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About this paper
Eleonora Giudici, Antonio Miele, Luca Mottola
The authors use a variational autoencoder (VAE) to learn spatial patterns in orbital FRAM errors and generate synthetic masks for application simulations. Reconstructions of observed masks reach precision 0.92 and recall 0.91; 10,000 generated masks have normalized Wasserstein distance 0.073 from the observed spatial distribution. These preliminary results cover one memory type, with no separate test set.
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