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...
Päätekijät: | Le, T, Igl, M, Rainforth, T, Jin, T, Wood, F |
---|---|
Aineistotyyppi: | Conference item |
Julkaistu: |
OpenReview
2018
|
Samankaltaisia teoksia
-
Monte Carlo variational auto-encoders
Tekijä: Thin, A, et al.
Julkaistu: (2021) -
Amortized Monte Carlo integration
Tekijä: Goliński, A, et al.
Julkaistu: (2019) -
On nesting Monte Carlo estimators
Tekijä: Rainforth, T, et al.
Julkaistu: (2019) -
Sequential Monte Carlo with transformations
Tekijä: Everitt, RG, et al.
Julkaistu: (2019) -
Sequential Monte Carlo samplers
Tekijä: Del Moral, P, et al.
Julkaistu: (2006)