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This post provides theoretical foundation behind the Weingarten map for curvature estimation along with its Python implementation for 2D images.
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Explaning key building blocks and main mathematical ideas behind the variational Auto Encoders -
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Lifting of raw data to higher dimensional feature space while maintaining localily. -
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Introduction into expectation maximization algorithm for fitting a mixture of parametric probabalistic models to data -
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This block covers ideas on energy based models starting physics via Gibbs distribution abd Restricted Boltzmann Machine.