This repo implements Denoising Diffusion Probabilistic Models (DDPM) in Pytorch

Collection of tutorials on diffusion models, step-by-step implementation guide, scripts for generating images with AI, prompt engineering guide, and resources for further learning.

The Land-Diffuser is a novel application of the Denoising Diffusion Probabilistic Model (DDPM) in the realm of 3D Talking Head generation from raw audio inputs.

Simple Version of Latent Diffusion Models

[ICASSP 2025]RAPID: Recognition of Any-Possible DrIver Distraction via Multi-view Pose Generation Models

Deep Learning for MRI Super-Resolution: A Comprehensive Survey

Medical Image Synthesis project (MedSyn). In-depth evaluation of the efffects of different synthesis models (i.e., CFG ccDDPM) for medical image synthesis for class balancing on image datasets (i.e., PathMNIST).

A probabilistic approach to wildfire spread prediction using a denoising diffusion model

A PyTorch from-scratch implementation of Denoising Diffusion Probabilistic Models (DDPM) and Denoising Diffusion Implicit Models (DDIM) sampling to generate 16x16 pixel art sprites.

Diffusion models from scratch and experiments

This project develops a robust medical image classification system working on latent representations of brain MRIs and leveraging Denoising Diffusion Probabilistic Models.

🖼️ Build and explore diffusion models for generating 16x16 pixel art sprites with a clear, from-scratch PyTorch implementation of DDPM and DDIM.

Course work from UCLA's ECE239 - Special Topics in Signals and Systems

This repository is an implementation of the denoising diffusion probabilistic model described in the following paper: https://arxiv.org/abs/2006.11239