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Found 5 papers, 4 papers with code
A Metric Learning Reality Check
Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods.
PyTorch Metric Learning
Deep metric learning algorithms have a wide variety of applications, but implementing these algorithms can be tedious and time consuming.
Unsupervised Domain Adaptation: A Reality Check
Interest in unsupervised domain adaptation (UDA) has surged in recent years, resulting in a plethora of new algorithms.
Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation
In a supervised setting, these validators evaluate checkpoints by computing accuracy on a validation set that has labels.
PyTorch Adapt
PyTorch Adapt is a library for domain adaptation, a type of machine learning algorithm that re-purposes existing models to work in new domains.
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