Pinned Repositories
Biogeographical_networks
Set of R scripts to construct and analyse biogeographical networks to detect bioregions
ccvae
The official codebase for Capturing label characteristics in VAEs
FixMatch-pytorch
Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
melbourne-datathlon-2020
PCfit
simclr
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
SimCLRv2-Pytorch
Pretrained SimCLRv2 models in Pytorch
suncet
Code to reproduce the results in the FAIR research papers "Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples" https://arxiv.org/abs/2104.13963 and "Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations" https://arxiv.org/abs/2006.10803
bloomingfield's Repositories
bloomingfield/Biogeographical_networks
Set of R scripts to construct and analyse biogeographical networks to detect bioregions
bloomingfield/ccvae
The official codebase for Capturing label characteristics in VAEs
bloomingfield/FixMatch-pytorch
Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
bloomingfield/melbourne-datathlon-2020
bloomingfield/PCfit
bloomingfield/simclr
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
bloomingfield/SimCLRv2-Pytorch
Pretrained SimCLRv2 models in Pytorch
bloomingfield/suncet
Code to reproduce the results in the FAIR research papers "Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples" https://arxiv.org/abs/2104.13963 and "Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations" https://arxiv.org/abs/2006.10803