Convolutional variational autoencoder for ground motion classification and generation toward efficient seismic fragility assessment

This study develops an end‐to‐end deep learning framework to learn and analyze ground motions (GMs) through their latent features, and achieve reliable GM classification, selection, and generation of simulated motions. The framework is composed of an analysis workflow that transforms and reconstruct...

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