Learn the distinctions between simple and stratified random sampling. Understand how researchers use these methods to ...

Researchers from South Korea improved solar panel dust detection by using SMOTE and stable diffusion (SD) augmentation, with SD boosting detection accuracy from 76.5% to 98.9% while preserving spatial ...

For decades, scientists have relied on a chemical fingerprint inside water molecules to determine where plants get their ...

In this study, the antifungal activity of endophytic yeast strains isolated from the generative parts of plants in Uzbekistan ...

Stephen Whitelam, a researcher whose work spans thermodynamic theory and machine learning, has described a framework for generating images from pure noise by using the physics of heat and motion ...

This project provides a complete pipeline for latent diffusion models, covering image dataset encoding into latents, training three different models with two distinct noise schedules, and sampling ...

Abstract: Hyperspectral images (HSIs) and multispectral images (MSIs) fusion is a hot topic in the remote sensing society. A high-resolution HSI (HR-HSI) can be obtained by fusing a low-resolution HSI ...

We introduce LML, an accelerated sampler for diffusion models leveraging the second-order Hessian geometry. Our LML implementation is completely compatible with the diffusers. This repository is the ...

Abstract: Diffusion models can generate a variety of high-quality images by modeling complex data distributions. Trained diffusion models can also be very effective image priors for solving inverse ...

Previous high-order solvers are unstable for guided sampling: Samples use the pre-trained DPMs on ImageNet 256 256 with a classifier guidance scale 8.0, varying different samplers (and different ...