AutoPool is an adaptive pooling function with a learnable parameter that allows it to smoothly interpolate between min-, mean-, softmax- and max-pooling. It is implemented as a Keras layer for easy integration in deep learning architectures.
AutoPool was originally developed for multiple instance learning from weakly labeled time-series data as detailed in the AutoPool paper.
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