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

Specifically, a cutting-edge 3D convolutional autoencoder is employed, which possesses the capability to estimate radio maps and quantify the uncertainty metric at each location. Then, an uncertainty ...

Therefore, this study proposes a sensor self-diagnosis design method based on the integration of binary convolutional autoencoder and Bayesian inference (BCAE-BI). First, to extract the redundancy ...

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