Autoencoder learns the data distribution and GAN learns by comparsion. …see more. Like. Like. Celebrate. Support. Love. Insightful. Funny. 6 How can you learn more about autoencoders and GANs?

This increased depth reduces the computational cost of representing some functions and it decreases the amount of training data required to learn some functions. The popular applications of ...

Electrocardiograms (ECG) are vital for diagnosing various cardiac conditions but are often corrupted by noise from multiple sources, which can hinder accurate interpretation. Denoising ECG signals is ...

This article introduces AnCoGen, a novel method that leverages a masked autoencoder to unify the analysis, control, and generation of speech signals within a single model. AnCoGen can analyze speech ...

Thus, we first used the autoencoder network, to roughly screen out the features to a proper dimension. The detailed two-stepwise feature selection procedure is described as follows: Step 1: We trained ...

KATE: K-Competitive Autoencoder for Text. word-embeddings autoencoder topic-modeling competitive-learning text-autoencoder. Updated Jan 29, 2020; Python; Improve this page Add a description, image, ...

Competitive endogenous RNA (ceRNA) regulatory networks (CENA) have advanced our understanding of noncoding RNAs’ roles in complex diseases, providing a theoretical basis for disease mechanisms.