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

Abstract: This work utilizes a variational autoencoder for channel estimation and evaluates it on real-world measurements. The estimator is trained solely on noisy channel observations and ...

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.

Reducio-VAE was developed to enable high compression ratio on videos, supporting efficient video generation. Existing 3D VAEs are generally extended from 2D VAE, which is designed for image generation ...