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docs/source/notebooks/0.5-Learning.ipynb

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"\n",
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"In this notebook, we start from the foundational application of predictive coding networks as a replacement for backpropagation {cite:p}`Song2024` based on **prospective configuration**, where the most likely neural activation is inferred before weight updates. We show that the variational updates that follow the prediction errors can replace prospective configuration based on gradient descent over the energy function of a predictive coding network, and validate this approach on the \"bear example\" from {cite:p}`Song2024`.\n",
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"\n",
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"```{figure} https://iiif.elifesciences.org/lax/27879%2Felife-27879-fig1-v3.tif/full/1500,/0/default.jpg\n",
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"```{figure} https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41593-023-01514-1/MediaObjects/41593_2023_1514_Fig1_HTML.png?as=webp\n",
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"---\n",
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"name: task\n",
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"---\n",

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