An autoencoder model is employed to predict behavioral patterns and visualize leisure consumption dynamics. Specifically, five key indicators—land diversity, population density, transportation ...

the model uses a pretrained 3D variational autoencoder to encode both the input video and the reference image. These latents are patchified, concatenated, and fed into the DiT, which processes them ...

Our proposed VA-VAE (Vision foundation model Aligned Variational AutoEncoder) significantly expands the reconstruction-generation frontier of latent diffusion models, enabling faster convergence of ...

We may receive compensation when you click on links to products we review. Please view our affiliate disclosure. TensorFlow is a popular open-source machine learning framework used to train neural ...

To overcome these limitations, this study introduces a novel supervised autoencoder generative adversarial network (SA-GAN) for data augmentation, leveraging advanced generative AI to create ...

This repository contains implementations of various machine learning algorithms from scratch, including Multi-Layer Perceptron (MLP), Gaussian Mixture Models (GMM), Principal Component Analysis (PCA), ...