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Improved gene regulatory network inference from single cell data with dropout augmentation

Fig 2

Appropriate amount of augmented dropout helps maintain model robustness and may contribute to better performance.

Color reflects the probability of dropout augmentation. The two thick lines represent two important conditions, 0% - no augmented dropout, and 10% - the default dropout augmentation level we recommend. Dashed lines show the default number of training iterations used in DeepSEM and DAZZLE.

Fig 2

doi: https://doi.org/10.1371/journal.pcbi.1013603.g002