| Causal generative models |
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| • | It
is easy to generate an |
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| unbiased
example at the |
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| leaf
nodes. |
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| • | It is
hard to compute the |
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| posterior
distribution over |
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| all
possible configurations |
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| of
hidden causes (except |
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| in
special cases) |
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| • | Given
samples from the |
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| posterior,
it is easy to |
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| learn
the local interactions |
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| hidden |
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| causes |
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| visible |
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| effects |
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