IEEE

Matrix-Inversion-Free Sparse Bayesian Learning for High-Resolution Radar Imagery via Improved Variational Inference

Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...
IEEE

Wavelet Domain Image Restoration and Parameters Estimation based on Variational Bayesian Method and Student-t Priors

Abstract: In this paper we proposed a novel algorithm for image restoration and parameters estimation with a wavelet domain Student-t priors using variational Bayesian method. Because the conventional ...
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.
Search Engine Land

How Bayesian testing lets Google measure incrementality with $5,000

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...
GitHub

SVG-T2I: Scaling up Text-to-Image Latent Diffusion Model

Important Note: This repository implements SVG-T2I, a text-to-image diffusion framework that performs visual generation directly in Visual Foundation Model (VFM) representation space, rather than ...