Efficient multifidelity likelihood-free Bayesian inference with adaptive computational resource allocation

Efficient multifidelity likelihood-free Bayesian inference with adaptive computational resource allocation

Likelihood-free Bayesian inference algorithms are popular methods for inferring the parameters of complex stochastic models with intractable likelihoods. These algorithms characteristically rely heavily on repeated model simulations. However, whenever the computational cost of simulation is even mod...

Полное описание

Библиографические подробности
Главные авторы:	Prescott, T, Warne, D, Baker, R
Формат:	Journal article
Язык:	English
Опубликовано:	Elsevier 2023

Схожие документы

Multifidelity approximate Bayesian computation
по: Prescott, T, и др.
Опубликовано: (2020)

Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes
по: Warne, D, и др.
Опубликовано: (2022)

Multifidelity approximate Bayesian computation with sequential Monte Carlo parameter sampling
по: Prescott, TP, и др.
Опубликовано: (2021)

Likelihood-free Bayesian inference for dynamic, stochastic simulators in the social sciences
по: Dyer, J
Опубликовано: (2022)

Adaptive active subspace-based efficient multifidelity materials design
по: Danial Khatamsaz, и др.
Опубликовано: (2021-11-01)

Non-myopic multipoint multifidelity Bayesian framework for multidisciplinary design
по: Francesco Di Fiore, и др.
Опубликовано: (2023-12-01)

Statistical inference : an integrated Bayesian/likelihood approach /
по: 482580 Aitkin, Murray A.
Опубликовано: (c201)

Rapid Bayesian inference for expensive stochastic models
по: Warne, DJ, и др.
Опубликовано: (2021)

Multifidelity importance sampling
по: Peherstorfer, Benjamin, и др.
Опубликовано: (2018)

Scaling Bayesian optimization for engineering design : lookahead approaches and multifidelity dimension reduction
по: Lam, Remi Roger Alain Paul
Опубликовано: (2018)

Publisher Correction: Non-myopic multipoint multifidelity Bayesian framework for multidisciplinary design
по: Francesco Di Fiore, и др.
Опубликовано: (2024-05-01)

Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds
по: Panagiotis Tsilifis, и др.
Опубликовано: (2022-09-01)

Multifidelity computing for coupling full and reduced order models.
по: Shady E Ahmed, и др.
Опубликовано: (2021-01-01)

FPGA Acceleration of the phylogenetic likelihood function for Bayesian MCMC inference methods
по: Bakos Jason D, и др.
Опубликовано: (2010-04-01)

A MATHEMATICAL AND COMPUTATIONAL FRAMEWORK FOR MULTIFIDELITY DESIGN AND ANALYSIS WITH COMPUTER MODELS
по: Allaire, Douglas L., и др.
Опубликовано: (2015)

Using Bayesian inference to understand the allocation of resources between sexual and asexual reproduction
по: Metcalf, C, и др.
Опубликовано: (2009)

Greedy nonlinear autoregression for multifidelity computer models at different scales
по: W. Xing, и др.
Опубликовано: (2020-08-01)

Use of Bayesian inference to estimate diversion likelihood in a PUREX facility
по: Rodewald, Oliver Russell
Опубликовано: (2013)

Multifidelity Uncertainty Propagation via Adaptive Surrogates in Coupled Multidisciplinary Systems
по: Chaudhuri, Anirban, и др.
Опубликовано: (2018)

Robust Field-level Likelihood-free Inference with Galaxies
по: Natalí S. M. de Santi, и др.
Опубликовано: (2023-01-01)

Multifidelity approaches for optimization under uncertainty
по: Ng, Leo W. T., и др.
Опубликовано: (2015)

Multifidelity Covariance Estimation Three Ways
по: Maurais, Aimee Elizabeth
Опубликовано: (2022)

Multifidelity Surrogate Models for Efficient Uncertainty Propagation Analysis in Salars Systems
по: Vasileios Christelis, и др.
Опубликовано: (2022-03-01)

Stochastic Volatility with Leverage: Fast and Efficient Likelihood Inference.
по: Omori, Y, и др.
Опубликовано: (2007)

Stochastic volatility with leverage: fast and efficient likelihood inference
по: Omori, Y, и др.
Опубликовано: (2007)

Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling
по: A. Gruber, и др.
Опубликовано: (2023-02-01)

An Optimization Centered Approach to Multifidelity Aircraft Design
по: Karcher, Cody Jacob
Опубликовано: (2023)

Multifidelity Methods for Design of Transition MetalComplexes
по: Janet, Jon Paul
Опубликовано: (2024)

Multifidelity Uncertainty Propagation in Coupled Multidisciplinary Systems
по: Chaudhuri, Anirban, и др.
Опубликовано: (2017)

Multifidelity Dimension Reduction via Active Subspaces
по: Lam, Remi R, и др.
Опубликовано: (2021)

Multifidelity methods for multidisciplinary design under uncertainty
по: Christensen, Daniel Erik
Опубликовано: (2013)

Convergence analysis of multifidelity Monte Carlo estimation
по: Peherstorfer, Benjamin, и др.
Опубликовано: (2021)

Optimized multifidelity machine learning for quantum chemistry
по: Vivin Vinod, и др.
Опубликовано: (2024-01-01)

Multifidelity multiobjective optimization for wake-steering strategies
по: J. Quick, и др.
Опубликовано: (2022-09-01)

Computational Neuropsychology and Bayesian Inference
по: Thomas Parr, и др.
Опубликовано: (2018-02-01)

Effectively using multifidelity optimization for wind turbine design
по: J. Jasa, и др.
Опубликовано: (2022-05-01)

Modified Multifidelity Surrogate Model Based on Radial Basis Function with Adaptive Scale Factor
по: Yin Liu, и др.
Опубликовано: (2022-06-01)

In all likelihood : statistical modelling and inference using likelihood /
по: 324497 Pawitan, Yudi
Опубликовано: (2001)

A practical guide to pseudo-marginal methods for computational inference in systems biology
по: Warne, DJ, и др.
Опубликовано: (2020)

A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation
по: Teh, Y, и др.
Опубликовано: (2007)