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    <loc>https://astroml-hackdays.org/seminars/classification</loc>
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    <lastmod>2020-12-07</lastmod>
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    <loc>https://astroml-hackdays.org/seminars/de-noising</loc>
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    <lastmod>2021-01-07</lastmod>
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      <image:title>Seminars - De-noising of images -11th Dec. 2020</image:title>
      <image:caption>Figure 1: What the effect of an autoencoder trained for de-noising can be. Source https://www.kaggle.com/anmour/convolutional-autoencoder-with-keras.</image:caption>
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    <loc>https://astroml-hackdays.org/seminars/anomaly-detection</loc>
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    <lastmod>2021-01-07</lastmod>
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      <image:title>Seminars - Anomaly Detection and (variational) autoencoders - 13th Nov. 2020</image:title>
      <image:caption>Figure 1: Different ways of visualising clusters of similar hand-written digits (MNIST dataset) with the first two components of PCA (Left) and the first two using T-SNE (right) (Source towarddatascience.com).</image:caption>
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      <image:title>Seminars - Anomaly Detection and (variational) autoencoders - 13th Nov. 2020</image:title>
      <image:caption>Figure 2: a typical architecture of an autoencoder. This type of architectures try to learn to reconstruct the input data via an encoding-decoding approach.</image:caption>
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