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Found 3 papers, 1 papers with code
Learning Generative Models of Tissue Organization with Supervised GANs
A key step in understanding the spatial organization of cells and tissues is the ability to construct generative models that accurately reflect that organization.
Deciding when to stop: Efficient stopping of active learning guided drug-target prediction
By analyzing the performance of the regression model on simulated data, we design stopping criteria for previously unseen experimental matrices.
Nuclei Segmentation In Microscope Cell Images: A Hand-Segmented Dataset And Comparison Of Algorithms
Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem.
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