k-stacke

cmiv-ai-course

Contains Jupyter Notebooks used during the exercise sessions at CMIVs (https://liu.se/en/research/center-for-medical-image-science-and-visualization-cmiv) AI course for radiologists and pathologists.

dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

facial_recognition

Greedy_InfoMax

Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations

MoCo-Pytorch

An unofficial Pytorch implementation of "Improved Baselines with Momentum Contrastive Learning" (MoCoV2) - X. Chen, et al.

representation-shift

This is the official code of the Representation Shift metric from "Measuring Domain Shift for Deep Learning in Histopathology" by Stacke et al.

siamese-triplet

Siamese and triplet networks with online pair/triplet mining in PyTorch

SimCLR

A PyTorch implementation of SimCLR based on the paper "A Simple Framework for Contrastive Learning of Visual Representations"

ssl-pathology

This is the official code for the paper Learning Represenations with Contrastive Self-Supervised Learning for Histopathology Applications

swav

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

k-stacke/ssl-pathology

This is the official code for the paper Learning Represenations with Contrastive Self-Supervised Learning for Histopathology Applications

k-stacke/representation-shift

This is the official code of the Representation Shift metric from "Measuring Domain Shift for Deep Learning in Histopathology" by Stacke et al.

k-stacke/Greedy_InfoMax

Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations

k-stacke/MoCo-Pytorch

An unofficial Pytorch implementation of "Improved Baselines with Momentum Contrastive Learning" (MoCoV2) - X. Chen, et al.

k-stacke/siamese-triplet

Siamese and triplet networks with online pair/triplet mining in PyTorch

k-stacke/SimCLR

A PyTorch implementation of SimCLR based on the paper "A Simple Framework for Contrastive Learning of Visual Representations"

k-stacke/cmiv-ai-course

Contains Jupyter Notebooks used during the exercise sessions at CMIVs (https://liu.se/en/research/center-for-medical-image-science-and-visualization-cmiv) AI course for radiologists and pathologists.

k-stacke/dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

k-stacke/facial_recognition

k-stacke/swav

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

k-stacke/yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

k-stacke/CONCH

A vision-language foundation model for computational pathology - Nature Medicine