tutorials

ComputationalPsychiatry · Sep 11, 2024 · 3ab4f9f · 3ab4f9f
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diff --git a/docs/source/images/cpc_tutorial_1.png b/docs/source/images/cpc_tutorial_1.png
diff --git a/docs/source/images/model_comparison.png → docs/source/images/cpc_tutorial_2.png b/docs/source/images/model_comparison.png → docs/source/images/cpc_tutorial_2.png
diff --git a/docs/source/learn.md b/docs/source/learn.md
@@ -187,17 +187,6 @@ A generalisation of the binary Hierarchical Gaussian Filter to multiarmed bandit
 
 ::::
 
-### Non-parametric predictive coding
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-::::{grid} 1 1 2 3
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-:::{grid-item-card} Self-organizing neural network using Dirichlet Process nodes
-:link: example_3
-:link-type: ref
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-:::
-::::
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 ## Exercises
 
 Hand-on exercises for theComputational Psychiatry Course (Zurich) to build intuition around the generalised Hierarchical Gaussian Filter, how to create and manipulate probabilistic networks, design an agent to perform a reinforcement learning task and use MCMC sampling for parameter inference and model comparison—about 4 hours.
@@ -209,14 +198,15 @@ Hand-on exercises for theComputational Psychiatry Course (Zurich) to build intui
 :::{grid-item-card} Introduction to the Generalised Hierarchical Gaussian Filter
 :link: hgf_exercises_1
 :link-type: ref
+:img-top: ./images/cpc_tutorial_1.png
 
 Theoretical introduction to the generative model of the generalised Hierarchical Gaussian Filter and presentation of the update functions (i.e. the first inversion of the model). 
 :::
 
 :::{grid-item-card} Applying the Hierarchical Gaussian Filter to reinforcement learning
 :link: hgf_exercises_2
 :link-type: ref
-:img-top: ./images/model_comparison.png
+:img-top: ./images/cpc_tutorial_2.png
 
 Practical application of the generalised Hierarchical Gaussian Filter to reinforcement learning problems and estimation of parameters through MCMC sampling (i.e. the second inversion of the model). 
 :::

diff --git a/...e/notebooks/Exercise_1_Introduction_to_the_generalised_hierarchical_gaussian_filter.ipynb b/...e/notebooks/Exercise_1_Introduction_to_the_generalised_hierarchical_gaussian_filter.ipynb
diff --git a/docs/source/notebooks/Exercise_2_Bayesian_reinforcement_learning.ipynb b/docs/source/notebooks/Exercise_2_Bayesian_reinforcement_learning.ipynb