Piotr Stępień's starred repositories
self-classifier
PyTorch implementation of "Self-Supervised Classification Network" from ECCV 2022
blitz-bayesian-deep-learning
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
ChainRules.jl
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
stable-diffusion
A latent text-to-image diffusion model
vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
essential-skills
Educational module 'Essential Skills for Machine Learning'
plastimatch
Plastimatch is an open source software for image computation. All development is currently done on GitLab.
segmentation_models_3D
Set of models for segmentation of 3D volumes
pylustrator
Visualisations of data are at the core of every publication of scientific research results. They have to be as clear as possible to facilitate the communication of research. As data can have different formats and shapes, the visualisations often have to be adapted to reflect the data as well as possible. We developed Pylustrator, an interface to directly edit python generated matplotlib graphs to finalize them for publication. Therefore, subplots can be resized and dragged around by the mouse, text and annotations can be added. The changes can be saved to the initial plot file as python code.
annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
git-re-basin
Code release for "Git Re-Basin: Merging Models modulo Permutation Symmetries"