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add (short) note about latent vectors
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examples/Intro_Amortized_Posterior_Estimation.ipynb

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"id": "biblical-tongue",
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"metadata": {},
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"source": [
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"Note about `z`: The inference network takes summary vectors as input and outputs latent vectors (`z`). The latent space is a lower-dimensional space that is assumed to capture the essential information about the parameters. It is essentially transforming the parameter space to the latent space (Gaussian in this case). \n",
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"\n",
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"We can inspect the shapes of the outputs as well:"
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]
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},

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