Self Supervised Learning Python Packages

pytorch-metric-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

lightly

A python library for self-supervised learning on images.

lightly-utils

A python library for self-supervised learning on images.

dipy

DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

mmcls

OpenMMLab Pre-training Toolbox and Benchmark

mmpretrain

OpenMMLab Pre-training Toolbox and Benchmark

s3prl

Self-Supervised Speech Pre-training and Representation Learning Toolkit

info-nce-pytorch

PyTorch implementation of the InfoNCE loss for self-supervised learning.

relic-pytorch

A simple PyTorch implementation of the Representation Learning via Invariant Causal Mechanisms self-supervised contrastive learning paper

byol-pytorch

Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

paddlespeech

Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

actinet

An activity classification model based on self-supervised learning for wrist-worn accelerometer data.

paddlespeech-feat

Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.

otx

OpenVINO™ Training Extensions: Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

libauc

LibAUC: A Deep Learning Library for X-Risk Optimization

biapy

Open source Python library for building bioimage analysis pipelines

accelbrainbeat

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

stepcount

Improved Step Counting via Foundation Models for Wrist-Worn Accelerometers

gigaam

Foundational Model for Speech Recognition Tasks

contrastive-learner

Self-supervised contrastive learning made simple

novae

Graph-based foundation model for spatial transcriptomics data. Zero-shot spatial domain inference, batch-effect correction, and many other features.

deepaudio-x

A python library to train Deep Neural Networks on various audio tasks using Self-Supervised backbones.

dive-into-graphs

A library for graph deep learning research

tabular-transformer

An end-to-end deep learning framework based on Transformer model, adapted for tabular data domain, support both supervised and self-supervised learning, used for regression, classification tasks.