IEEE

Application of variational autoencoder network to real-time prediction of steel crown in the hot strip rolling mill process

Abstract: In the hot strip rolling mill (HSRM) process, accurate prediction and control of the strip crown are critical for quality assurance. In order to cope with this challenge, this study designed ...
IEEE

Research on Fault Detection Methods of High-Speed Railway Passenger Transportation Management System Using Autoencoder and Variational Autoencoder

Abstract: The high-speed rail passenger transportation management system, as an integral part of modern railway transportation, bears the crucial responsibility of facilitating people's travel.
GitHub

ti2ni1m/Image-Generation-with-Conditional-Variational-Autoencoder-C-VAE-and-Conditional-GAN-C-GAN-

In this project, I aim to create a set of images of Kuzushiji Japanese characters via the Kuzushiji-49 dataset using 2 graphical models which are Conditional-Variational Autoencoder(C-VAE), and ...
Visual Studio Magazine

Generating Synthetic Data Using a Variational Autoencoder with PyTorch

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...
GitHub

MMO-VAE: Variational AutoEncoder with Mask-Guided Multi-Objective Optimization for de novo Drug Design

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 ...
Microsoft

Crystal Diffusion Variational Autoencoder for Periodic Material Generation

Generating the periodic structure of stable materials is a long-standing challenge for the material design community. This task is difficult because stable materials only exist in a low-dimensional ...