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 ...
GitHub

Dynamical Dual Latent Space Variational Autoencoder Model with Koopman Constraint for Semi-Supervised Soft Sensor Application

├── data_pre/ # Data preprocessing modules │ ├── data_pre.py # Data preprocessing script │ └── dataset.py # Dataset class definition ├── dataset/ # Data directory │ ├── SRU_data.npy # Process data in ...
IEEE

Utilizing uncertainty quantification variational autoencoders in inverse problems with applications in photoacoustic tomography

Abstract: There is an increasing interest in utilizing machine learning methods in image processing and inverse problems. A significant part of the current work in inverse problems has, however, ...
Nature

Geostatistical Inversion for Subsurface Characterization Using Stein Variational Gradient Descent With Autoencoder Neural Network: An Application to Geologic Carbon Sequestration

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...
GitHub

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

In our recent paper, we propose VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. Several recent end-to-end text-to-speech (TTS) models enabling single ...
Scientific Research Publishing

Yuan, Z. and Dong, D.M. (2022) Near-Infrared Spectroscopy Measurement of Contrastive Variational Autoencoder and Its Application in the Detection of Liquid Sample. Spectroscopy ...

ABSTRACT: Current high-dimensional feature screening methods still face significant challenges in handling mixed linear and nonlinear relationships, controlling redundant information, and improving ...
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 ...