Transfer learning and semi-supervised learning (MixMatch) on noisy Imagewoof data using PyTorch.
-
Updated
Feb 24, 2021 - Jupyter Notebook
Transfer learning and semi-supervised learning (MixMatch) on noisy Imagewoof data using PyTorch.
Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"
an unofficial PyTorch implementation of "MixMatch: A Holistic Approach to Semi-Supervised Learning" on IMDB
Reproduction of "MixMatch - A Holistic Approach to Semi-Supervised Learning" in Pytorch.
A semi-supervised learning algorithm
Semi-supervised learning techniques (pseudo-label, mixmatch, and co-training) for pre-trained BERT language model amidst low-data regime based on molecular SMILES from the Molecule Net benchmark.
Advanced Scheduling Algorithm for Managing Pseudo Labels in Semi-Supervised Learning
CIFAR10 PyTorch implementation of "MixMatch - A Holistic Approach to Semi-Supervised Learning"
Implementation of semi-supervised learning using PyTorch Lightning
An unofficial PyTorch implementation of MixMatch - A Holistic Approach to Semi-Supervised Learning
MixMatch Domain Adaptation: Prize-winning solution for both tracks of VisDA 2019 challenge
A Pytorch implementation of the MixMatch algorithm developed by google-research.
PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch
Add a description, image, and links to the mixmatch topic page so that developers can more easily learn about it.
To associate your repository with the mixmatch topic, visit your repo's landing page and select "manage topics."