byol

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

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

BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representation

Self-Supervised Learning in PyTorch

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

PyTorch implementation of "Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning" with DDP and Apex AMP

Collections of self-supervised methods, based on cvpods.

Toolkit for training and evaluating Self-Supervised Learning (SSL) frameworks for Speaker Verification (SV).

SERAB: a multi-lingual benchmark for speech emotion recognition

Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples

[NeurIPS 2023 (Spotlight)] Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts

PyTorch Implementation of Self-Supervised Learning models

A python library for self-supervised learning

Codebase for Imperial MSc AI Individual Project - Self-Supervised Learning for Audio Inference

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

Tracks VM and sole-tenant node usage for the purpose of license reporting

This repo reproduces results of "Understanding Self-Supervised Learning Dynamics without Contrastive Pairs" paper (https://arxiv.org/pdf/2102.06810.pdf)

Bootstrap Your Own Latent (BYOL) in PyTorch

Simple Pytorch Implementation of BYOL: Bootstrap Your Own Latent(https://arxiv.org/abs/2006.07733) [Colab Version Available]

BYOL (Bootstrap Your Own Latent), implemented from scratch in Pytorch