Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

"Deep Generative Modeling": Introductory Examples

PyTorch implementation of realNVP

PyTorch implementation of normalizing flow models

Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"

Course notes

One-step image-to-image with Stable Diffusion turbo: sketch2image, day2night, and more

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan…

Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.

BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Joint variational Autoencoders for Multimodal Imputation and Embedding (JAMIE)

Unofficial PyTorch Implementation of Denoising Diffusion Probabilistic Models (DDPM)

PyTorch Tutorial for Deep Learning Researchers

List of software packages for multi-omics analysis

Unofficial implementation of Palette: Image-to-Image Diffusion Models by Pytorch

Code for comparison of multimodal VAE models

Code and Data for "Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features"

[CVPR 2022] Official PyTorch Implementation for DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models

Experiments with Deep Learning

example code illustrating analyses of semi-competing risks data

Applied Deep Learning Course

Implement a MNIST(also minimal) version of denoising diffusion probabilistic model from scratch.The model only has 4.55MB.