Auto-encoding sequential Monte Carlo

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...

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Bibliografiske detaljer
Main Authors:	Le, T, Igl, M, Rainforth, T, Jin, T, Wood, F
Format:	Conference item
Udgivet:	OpenReview 2018

Lignende værker

Monte Carlo variational auto-encoders
af: Thin, A, et al.
Udgivet: (2021)

Amortized Monte Carlo integration
af: Goliński, A, et al.
Udgivet: (2019)

On nesting Monte Carlo estimators
af: Rainforth, T, et al.
Udgivet: (2019)

Sequential Monte Carlo with transformations
af: Everitt, RG, et al.
Udgivet: (2019)

Sequential Monte Carlo samplers
af: Del Moral, P, et al.
Udgivet: (2006)

Controlled sequential Monte Carlo
af: Heng, J, et al.
Udgivet: (2020)

Kernel sequential Monte Carlo
af: Schuster, I, et al.
Udgivet: (2017)

Sequential Monte Carlo in sequence
af: Nur Nabihah Rusyda, Roslan, et al.
Udgivet: (2022)

Interacting particle Markov chain Monte Carlo
af: Doucet, A, et al.
Udgivet: (2016)

Sequential Monte Carlo methods for diffusion processes
af: Jasra, A, et al.
Udgivet: (2009)

Efficient Sequential Monte Carlo Using Interpolation
af: Hover, Franz S.
Udgivet: (2010)

Sequential Monte Carlo methods for demographic inference
af: Henderson, D
Udgivet: (2017)

Parameter estimation using sequential monte carlo /
af: Mohd. Fariduddin Mukhtar, 1987-, et al.
Udgivet: (2012)

Sequential Monte Carlo with highly informative observations
af: Del Moral, P, et al.
Udgivet: (2015)

Sequential Monte Carlo-guided ensemble tracking.
af: Yuru Wang, et al.
Udgivet: (2017-01-01)

Online sequential Monte Carlo smoother for partially observed diffusion processes
af: Pierre Gloaguen, et al.
Udgivet: (2018-02-01)

An information-theoretic analysis of resampling in Sequential Monte Carlo
af: Huggins, Jonathan H. (Jonathan Hunter)
Udgivet: (2014)

On sequential Monte Carlo sampling methods for Bayesian filtering
af: Doucet, A, et al.
Udgivet: (2000)

Fast sequential Monte Carlo methods for counting and optimization /
af: Rubinstein, Reuven Y., author, et al.
Udgivet: (2014)

SEQUENTIALLY INTERACTING MARKOV CHAIN MONTE CARLO METHODS
af: Brockwell, A, et al.
Udgivet: (2010)

On adaptive resampling strategies for sequential Monte Carlo methods
af: Del Moral, P, et al.
Udgivet: (2012)

vSMC: Parallel Sequential Monte Carlo in C++
af: Yan Zhou
Udgivet: (2015-01-01)

Sequential monte carlo methods To train neural network models
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Udgivet: (2000)

Efficient block sampling strategies for sequential Monte Carlo methods
af: Doucet, A, et al.
Udgivet: (2006)

Sequential Monte Carlo Methods to Train Neural Network Models
af: Freitas, D, et al.
Udgivet: (2000)

Interacting sequential Monte Carlo samplers for trans-dimensional simulation
af: Jasra, A, et al.
Udgivet: (2008)

Sequential monte carlo techniques for EEG dipole placing and tracking
af: Mohseni, H, et al.
Udgivet: (2008)

Sequential Monte Carlo for model selection and estimation of neural networks
af: Andrieu, C, et al.
Udgivet: (2000)

An adaptive sequential Monte Carlo method for approximate Bayesian computation
af: Del Moral, P, et al.
Udgivet: (2011)

An adaptive sequential Monte Carlo method for approximate Bayesian computation
af: Del Moral, P, et al.
Udgivet: (2012)

Parameter estimation using sequential monte carlo [electronic resource] /
af: Mohd. Fariduddin Mukhtar, 1987-
Udgivet: (2012)

Evolutionary Sequential Monte Carlo Samplers for Change-Point Models
af: Arnaud Dufays
Udgivet: (2016-03-01)

A sequential Monte Carlo approach to gene expression deconvolution.
af: Oyetunji E Ogundijo, et al.
Udgivet: (2017-01-01)

Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals
af: Marzouk, Youssef M
Udgivet: (2020)

Stability of sequential Monte Carlo samplers via the Foster-Lyapunov condition
af: Jasra, A, et al.
Udgivet: (2008)

Sequential Monte Carlo tracking schemes for maneuvering targets with passive ranging
af: Malcolm, W, et al.
Udgivet: (2002)

Sequential Monte Carlo implementation of the PHD filter for multi-target tracking
af: Vo, B, et al.
Udgivet: (2003)

Stability of sequential Monte Carlo samplers via the Foster-Lyapunov condition
af: Jasra, A, et al.
Udgivet: (2008)

Multifidelity approximate Bayesian computation with sequential Monte Carlo parameter sampling
af: Prescott, TP, et al.
Udgivet: (2021)

Detecting Simulated Nosocomial Disease Outbreaks with Sequential Monte Carlo Methods
af: Dr Conor Rosato
Udgivet: (2025-03-01)