First, we will need a way for a Distribution (our in-code representation
of a data model) to specify to the system whether it wants to explicitly
represent its latents, or collapse (marginalize) them.
• For distributions that explicitly represent their latents, logp score should
return the conditional likelihood of the accumulated data given the current
value of the parameter θ, and logp should return the likelihood of a new
datapoint x given θ
ThomasColthurst
commented
1 week ago
First, we will need a way for a Distribution (our in-code representation of a data model) to specify to the system whether it wants to explicitly represent its latents, or collapse (marginalize) them.
• For distributions that explicitly represent their latents, logp score should return the conditional likelihood of the accumulated data given the current value of the parameter θ, and logp should return the likelihood of a new datapoint x given θ