Sample-efficient active learning for materials informatics using integrated posterior variance

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This time, before we perturb the input image, we take the value given by the threshold matrix and divide it by , where is the number of levels for each colour component. As a result, each pixel is perturbed just enough to cover the minimal distance between two colours in the palette. Since the entire palette is evenly distributed across colour space, we only need to modify the range of perturbation along each axis. The dithering equation then becomes:

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