GitHub

Transformer-based Denoising AutoEncoder for Sentence Transformers Unsupervised pre-training

The acquisition of sentence embeddings often necessitates a substantial volume of labeled data. However, in many cases and fields, labeled data is rarely accessible, and the procurement of such data ...
IEEE

Representation Learning With Dual Autoencoder for Multi-Label Classification

Abstract: Multi-label classification aims to deal with the problem that an object may be associated with one or more labels, which is a more difficult task due to the complex nature of multi-label ...
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.
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 ...