This repository presents an implementation of a Variational Autoencoder (VAE) tailored for the generation and analysis of protein structures. The documentation provided here outlines the conceptual ...

In this paper, we propose a marginalized graph autoencoder with subspace structure preserving, which adds a self-expressive layer to reveal the clustering structure of node attributes based on the ...

This letter introduces a new denoiser that modifies the structure of denoising autoencoder (DAE), namely noise learning based DAE (nlDAE). The proposed nlDAE learns the noise of the input data. Then, ...

The overall structure of the PyTorch autoencoder anomaly detection demo program, with a few minor edits to save space, is shown in Listing 3. I prefer to indent my Python programs using two spaces ...

Given a sequence of video frames as input, the Video Autoencoder extracts a disentangled representation of the scene including: (i) a temporally-consistent deep voxel feature to represent the 3D ...

Keywords: neural segmentation, SEM image, masked autoencoder, image segmentation, self-supervised learning. Citation: Cheng A, Shi J, Wang L and Zhang R (2023) Learning the heterogeneous ...

To ensure a fair comparison with Mostafa’s proposed CAE model, we maintained consistency in data processing, using T1-weighted MRI slice images of the healthy control group for autoencoder ...

Dynamic allostery on proteins, triggered by regulator binding or chemical modifications, transmits information from the binding site to distant regions, dramatically altering protein function. It is ...