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DISCOVER visual interpretability paper is published!

DISCOVER is a generative model for visual interpretability of image-based classification models. DISCOVER’s disentanglement module enables visual interpretation of one semantic classification-driving feature at a time. We applied DISCOVER to interpret classification of the morphology quality of in vitro fertilization embryos.


Project led by Oded Rotem in collaboration with AIVF.








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 Assaf Zaritsky lab of computational cell dynamics, applying data science to microscopy cell images since 2018

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