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 ...

This letter concerns control-oriented and structure-preserving learning of low-dimensional approximations of high-dimensional physical systems, with a focus on mechanical systems. We investigate the ...

Swapping Autoencoder consists of autoencoding (top) and swapping (bottom) operation.Top: An encoder E embeds an input (Notre-Dame) into two codes.The structure code is a tensor with spatial dimensions ...

The mean DOPE score decreases from 1-layer VAE to 4-layer VAE, indicating the increased ability to generate protein conformations that have lower potential energy. This ability does not increase ...

In this article, we will cover a simple Long Short Term Memory autoencoder with the help of Keras and python. What is an LSTM autoencoder? LSTM autoencoder is an encoder that makes use of LSTM encoder ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, they Announced the deep optimization of stacked sparse autoencoders through the DeepSeek open ...

This paper innovatively proposes a temporal–spatial pyramid variational autoencoder (TS-PVAE) model for the nonlinear temporal–spatial feature pyramid extraction from multirate data. This structure ...