IEEE

Target-Embedding Autoencoder With Knowledge Distillation for Multi-Label Classification

Abstract: In the task of multi-label classification, it is a key challenge to determine the correlation between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most ...
IEEE

Attention-Empowered Residual Autoencoder for End-to-End Communication Systems

Abstract: Channel autoencoders adopt neural networks to represent and optimize previous block-driven communication systems from an end-to-end perspective. The existing deep fully connected autoencoder ...
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.
GitHub

Visualize the Latent Space of an Autoencoder using matplotlib

What’s the Latent Space ? An Autoencoder is made of two components: an Encoder & a Decoder. The Encoder brings the input data from a high dimensional representation to a bottleneck layer, where the ...