Popular GitHub Repositories for Simclr

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.

[Nature Machine Intelligence 2024] Code and evaluation repository for the paper

(Minimally) implements SimCLR (https://arxiv.org/abs/2002.05709) in TensorFlow 2.

Awesome-Representation-Learning-CV-PaperAndCodes, lasted development in the representation learning area.

TensorFlow Implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

This is the official repository of L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning github

topological deep learning

Codebase for Imperial MSc AI Group Project: How Well Do Self-Supervised Models Transfer to Medical Imaging?

Official repo for the following paper: Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training (SCPT) (ECML PKDD DAMI '23)

Clean, reproducible, boilerplate-free deep learning project template.

Adversarial Meta Learning on Contrastive Learning model SimCLR. Aiming to robustify original SimCLR with data augmentation and adversarial training.

Finetuning and clustering library for image perceptual similarity models.

A tutorial of implementing/training/finetuning the SimCLR model with Pytorch Lightning.

Repository containing source code of the master thesis: "Synthetic Data and Contrastive Self-Supervised Training for Central Sulcus Segmentation"

PyTorch implementation of SimCLR: Simple Framework for Contrastive Learning of Visual Representations by Chen et al. (2020)