IEEE

Convolutional Variational Autoencoder for Anomaly Detection in On-Load Tap Changers

Abstract: Transformer outages significantly impact the reliability and cost efficiency of power systems. Studies indicate that approximately 30% of transformer failures stem from issues with on-load ...
IEEE

Effect of Integrating Variational Autoencoder with SENet on Dimensionality Reduction in Driving Behavior Learning

Abstract: Dimensionality reduction using Variational Autoencoder (VAE) is widely employed in learning diverse state representations, such as in autonomous driving tasks. Conventional VAE-based ...
GitHub

Variational AutoEncoder Tiny Model

This project demonstrates the use of a Variational AutoEncoder (VAE) to learn a latent space representation of simple synthetic data: black-and-white images of circles with varying radius, x, and y ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.