Tremendous studies have been produced to use molecular biology prospectives and different machine learning ... Voting-Based Stacked Denoising Auto-Encoders (VSDA) The proposed model was studied for ...

In order to eliminate the dimensional influence between different features and improve the effectiveness of model training ... Between the encoder and decoder, the autoencoder learns the feature ...

One promising approach is the sparse autoencoder (SAE), a deep learning ... A single neuron might activate for thousands of different concepts, and a single concept might activate a broad range ...

The Cross Auto-Encoder ... utilizing different loss functions for training, sharing parameters, and decoding the reconstructed character. Our extensive experiments on the expanded inscription dataset ...

The auto-encoder in the model replaces the coding and modulation ... to short and medium block lengths ( L ≤ 100 ) and different code rates. The experimental results show that the DRSN-AE autoencoder ...

To address this issue, we propose an importance-weighted sampling enhanced Variational Autoencoder (VAE ... within constant fitting times on different sizes, comparable to what Urban and Bauer (2021) ...