However, a fundamental flaw exists in Variational Autoencoder (VAE) based approaches. Specifically, the objective function of VAE (reconstruction loss), deviates from its primary objective (i.e ...

This repository contains the implementation of MMO-VAE, a Variational AutoEncoder (VAE) with mask-guided multi-objective optimization for de novo drug design. Implements KLD Sigmoid Annealing and ...

2.1 Improvement of the objective function of the VAE network Inspired ... At the same time, the loss function of the variational autoencoder (VAE) is improved. By adding a hyperparameter β to the ...

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A variational autoencoder (VAE) is a deep neural system that can be ... file of UCI digits data into memory as a two-dimensional array using the NumPy loadtxt() function. The pixel values are ...

A Variational Autoencoder (VAE) in neural networks works ... and a decoder that reconstructs the original data. VAEs use a loss function with a reconstruction term and a regularization term ...