Functional Autoencoders for Amplitude-Phase Representation Learning
An unsupervised framework for functional data that spans both univariate and multivariate cases, with emphasis on the multivariate setting, and factorizes the latent space into separate amplitude and phase embeddings derived from all channels is proposed.
Pei-Da Wu, X. Xiong, Peng-Cheng Zeng
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