representation-learning-papers-in-single-cell-microscopy

This repository holds an updated track of representation learning papers with application in single cell microscopy data.

review

Self-Supervised Representation Learning: Introduction, Advances and Challenges [paper]
Image-based cell phenotyping with deep learning [paper]

Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting [paper][code]
Self-supervised dense representation learning for live-cell microscopy with time arrow prediction [paper] [code]
Self-supervised deep learning encodes high-resolution features of protein subcellular localization [paper] [code]
Deep Representation Learning for Image-Based Cell Profiling [paper]
Unbiased single-cell morphology with self-supervised vision transformers [paper] [code]
Microsnoop: A generalist tool for microscopy image representation [paper] [code]
Self-Supervised Representation Learning for High-Content Screening [paper]

Weakly Supervised Learning of Single-Cell Feature Embeddings [paper] [code]
Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology [paper] [code]
Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels [paper] [code]