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This repository contains my final submission for the COMP3547 Deep Learning module assignment at Durham University in the academic year 2022/2023. The project focuses on diffusion-based models and their application in synthesising new, unique images, which could plausibly come from a training data set. Final grade received was 71/100.
A demo of how Generative Diffusion Models work considering the DDPM implementation. This demo is an addon for my Bayesian Statistics course's final report - academic year 2023/2024
A PyTorch-based repository for training and experimenting with diffusion models on the MNIST dataset. It includes a customizable U-Net model, various neural network blocks, and training scripts with optional TensorBoard integration for monitoring the training process and results.