Auto-encoding sequential Monte Carlo
We build on auto-encoding sequential Monte Carlo (AESMC): a method for model and proposal learning based on maximizing the lower bound to the log marginal likelihood in a broad family of structured probabilistic models. Our approach relies on the efficiency of sequential Monte Carlo (SMC) for perfor...
मुख्य लेखकों: | Le, T, Igl, M, Rainforth, T, Jin, T, Wood, F |
---|---|
स्वरूप: | Conference item |
प्रकाशित: |
OpenReview
2018
|
समान संसाधन
-
Monte Carlo variational auto-encoders
द्वारा: Thin, A, और अन्य
प्रकाशित: (2021) -
Amortized Monte Carlo integration
द्वारा: Goliński, A, और अन्य
प्रकाशित: (2019) -
On nesting Monte Carlo estimators
द्वारा: Rainforth, T, और अन्य
प्रकाशित: (2019) -
Sequential Monte Carlo with transformations
द्वारा: Everitt, RG, और अन्य
प्रकाशित: (2019) -
Sequential Monte Carlo samplers
द्वारा: Del Moral, P, और अन्य
प्रकाशित: (2006)