Mitigating Model Misspecification with Variational Bayesian Inference

QR Code

Mitigating Model Misspecification with Variational Bayesian Inference

Learning dynamical systems from data is an important modelling problem in which one approximates the underlying equations of motion governing the evolution of some system. The conventional approach involves utilising a dynamical model, often derived from expert knowledge to accurately replicate the...

Full description

Bibliographic Details
Main Author:	Krissaane, Ines
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2024
Subjects:	Model Misspecification Generalised Variational Inference dynamic modelling Bayesian statisics
Online Access:	https://eprints.nottingham.ac.uk/79405/

Similar Items

Declarative modelling for Bayesian inference by shallow embedding
by: Nilsson, Henrik, et al.
Published: (2014)

Topics in Bayesian inference and model assessment for partially observed stochastic epidemic models
by: Aristotelous, Georgios
Published: (2020)

A tutorial introduction to Bayesian inference for stochastic epidemic models using Approximate Bayesian Computation
by: Kypraios, Theodore, et al.
Published: (2017)

GARCH dependence in extreme value models with Bayesian inference
by: Zhao, X., et al.
Published: (2011)

Bayesian Inference for Stochastic Epidemic Models using Markov chain Monte Carlo Methods
by: Demiris, Nikolaos
Published: (2004)

Bayesian nonparametric inference for stochastic epidemic models
by: Xu, Xiaoguang
Published: (2015)

On noise, uncertainty and inference for computational diffusion MRI
by: Manzano Patron, Jose Pedro
Published: (2023)

Modelling and Bayesian analysis of the Abakaliki smallpox data
by: Stockdale, Jessica E., et al.
Published: (2017)

Characterisation of glioblastoma sub-populations using mathematical modelling and inference
by: Morris, Bethan Edith
Published: (2022)

Exact Bayesian inference for the Bingham distribution
by: Fallaize, Christopher J., et al.
Published: (2016)

Bayesian nonparametric methods for individual-level stochastic epidemic models
by: Seymour, Rowland G.
Published: (2020)

Generalisation of prior information for rapid Bayesian time estimation
by: Roach, Neil, et al.
Published: (2016)

Bayesian perspectives on statistical modelling
by: Polson, Nicholas G.
Published: (1988)

Bayesian nonparametrics for stochastic epidemic models
by: Kypraios, Theodore, et al.
Published: (2018)

Estimating matrix travel light vehicle observations by volume sleeve approach inference bayes
by: Abusini, Sobri, et al.
Published: (2016)

Bayesian calibration, validation and uncertainty quantification for predictive modelling of tumour growth: a tutorial
by: Collis, Joe, et al.
Published: (2017)

A Bayesian model for the unlabelled size-and-shape analysis
by: Sajib, Anamul
Published: (2018)

Nonlinear Bayesian Filtering Using the Unscented Linear Fractional Transformation Model
by: Pasha, S., et al.
Published: (2010)

Bayesian edge-detection in image processing
by: Stephens, David A.
Published: (1990)

Risk prediction model for knee pain in the Nottingham Community: a Bayesian modeling approach
by: Fernandes, Gwen Sascha, et al.
Published: (2017)

Estimation of parameters in mean-reverting stochastic systems
by: Tian, T., et al.
Published: (2014)

Theoretical approaches to identify the potent scaffold for human sirtuin1 activator: Bayesian modeling and density functional theory
by: Sakkiah, S., et al.
Published: (2014)

Forecasting tourism demand with an improved mixed data sampling model
by: Wen, Long, et al.
Published: (2020)

Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements
by: Iglesias, Marco, et al.
Published: (2018)

Bayesian optimization of large-scale biophysical networks
by: Hadida, Jonathan, et al.
Published: (2018)

Supporting local flood risk decision-making using participatory modelling
by: Maskrey, Shaun Andrew
Published: (2017)

Learning priors for Bayesian perception in normal and atypical development
by: McKeown, Lucy
Published: (2024)

A novel fault detection and diagnostic petri net methodology for dynamic systems
by: Badmus, Taofeeq Alabi
Published: (2025)

Management interventions in dairy herds: exploring within herd uncertainty using an integrated Bayesian model
by: Green, Martin J., et al.
Published: (2009)

Kalman-like Inversion with ODE/SDE Formulations and Adaptive Algorithms
by: Yang, Yuchen
Published: (2020)

Bayesian minimax estimation of the normal model with incomplete prior covariance matrix specification
by: Pham, DucSon, et al.
Published: (2010)

Likelihood Inference In Parallel Systems Regression Models With Censored Data
by: S.M.Baklizi, Ayman
Published: (1997)

Bayesian assessment of an existing bridge - a case study
by: Jacinto, Luciano, et al.
Published: (2015)

CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts
by: Testa, Alison, et al.
Published: (2015)

Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
by: Ahmed, Al Omari Mohammed
Published: (2013)

Design exploration with stochastic models of variation: Comparing two examples from facade subdivision
by: Datta, Sambit
Published: (2013)

New mathematical approaches to the quantification of uncertainty affecting the measurement of U-value
by: De Simon, Lia
Published: (2017)

Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
by: Googhari, Shahram Karimi
Published: (2007)

Bayesian inference of Weibull distribution for right and interval censored data
by: Guure, Chris Bambey
Published: (2013)

A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters
by: Gerstgrasser, Matthias, et al.
Published: (2016)