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cs.CV2023
Minimum Description Length Clustering to Measure Meaningful Image Complexity
Louis Mahon, Thomas Lukasiewicz
Existing image complexity metrics cannot distinguish meaningful content from noise. This means that white noise images, which contain no meaningful information, are judged as highl…
cs.LG2023
Correcting Flaws in Common Disentanglement Metrics
Louis Mahon, Lei Shah, Thomas Lukasiewicz
Recent years have seen growing interest in learning disentangled representations, in which distinct features, such as size or shape, are represented by distinct neurons. Quantifyin…
cs.LG2023
Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation
Louis Mahon, Thomas Lukasiewicz
Online deep clustering refers to the joint use of a feature extraction network and a clustering model to assign cluster labels to each new data point or batch as it is processed. W…