Approaching (Almost) Any Machine Learning Problem中译版，在线文档地址：https://ytzfhqs.github.io/AAAMLP-CN/

A family of open-sourced Mixture-of-Experts (MoE) Large Language Models

A curated list of papers on the applications of RWKV in computer vision.

A hyperparameter optimization framework

Materials for the Hugging Face Diffusion Models Course

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

[MICCAI 2023] MedNeXt is a fully ConvNeXt architecture for 3D medical image segmentation.

DoseDiff: Distance-aware Diffusion Model for Dose Prediction in Radiotherapy

A python (Pytorch) implementation of Beam Dose Decomposition for Dose Prediction [MICCAI 2022]

This is the codebase for MD-Dose: A Diffusion Model based on the Mamba for Radiotherapy Dose Prediction

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

This is the official Pytorch implementation of the paper "Diffusion Models for Implicit Image Segmentation Ensembles".

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)

Develop plan optimization models for knowledge-based planning in radiotherapy

Domain knowledge driven 3D radiation dose prediction [PMB'22]

An elegant \LaTeX\ résumé template. 大陆镜像 https://gods.coding.net/p/resume/git

A community effort to develop an open standard library for Medical Physics in Python. Building quality transparent software together via peer review and open source distribution. Open code is bette…

Tools to help with the conversion of DICOM images, RT Structures, and dose to useful Python objects. Essentially DICOM to NumPy and SimpleITK Images

Fast and differentiable MS-SSIM and SSIM for pytorch.

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

Pseudo Labeling for Neural Networks and Logistic Regression/SVMs ( Based on "Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks")

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

A framework for data augmentation for 2D and 3D image classification and segmentation