Survey of multifidelity methods in uncertainty propagation, inference, and optimization

B Peherstorfer, K Willcox, M Gunzburger - Siam Review, 2018 - SIAM
In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …

A survey of Monte Carlo methods for parameter estimation

D Luengo, L Martino, M Bugallo, V Elvira… - EURASIP Journal on …, 2020 - Springer
Statistical signal processing applications usually require the estimation of some parameters
of interest given a set of observed data. These estimates are typically obtained either by …

An optimization-centric view on Bayes' rule: Reviewing and generalizing variational inference

J Knoblauch, J Jewson, T Damoulas - Journal of Machine Learning …, 2022 - jmlr.org
We advocate an optimization-centric view of Bayesian inference. Our inspiration is the
representation of Bayes' rule as infinite-dimensional optimization (Csisz´ r, 1975; Donsker …

Inversion of surface deformation data for rapid estimates of source parameters and uncertainties: A Bayesian approach

M Bagnardi, A Hooper - Geochemistry, Geophysics …, 2018 - Wiley Online Library
New satellite missions (eg, the European Space Agency's Sentinel‐1 constellation),
advances in data downlinking, and rapid product generation now provide us with the ability …

Strong constraints on the gravitational law from Gaia DR3 wide binaries

I Banik, C Pittordis, W Sutherland… - Monthly Notices of …, 2024 - academic.oup.com
We test Milgromian dynamics (MOND) using wide binary stars (WBs) with separations of 2–
30 kAU. Locally, the WB orbital velocity in MOND should exceed the Newtonian prediction …

Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation

JA Vrugt - Environmental Modelling & Software, 2016 - Elsevier
Bayesian inference has found widespread application and use in science and engineering
to reconcile Earth system models with data, including prediction in space (interpolation) …

A student's guide to Bayesian statistics

B Lambert - 2018 - torrossa.com
Untitled Page 1 Page 2 A Student’s Guide to BAYESIAN STATISTICS Page 3 Sara Miller
McCune founded SAGE Publishing in 1965 to support the dissemination of usable knowledge …

Role of atmospheric oxidation in recent methane growth

M Rigby, SA Montzka, RG Prinn… - Proceedings of the …, 2017 - National Acad Sciences
The growth in global methane (CH4) concentration, which had been ongoing since the
industrial revolution, stalled around the year 2000 before resuming globally in 2007. We …

[LIBRO][B] Bayesian estimation of DSGE models

EP Herbst, F Schorfheide - 2016 - degruyter.com
Dynamic stochastic general equilibrium (DSGE) models have become one of the
workhorses of modern macroeconomics and are extensively used for academic research as …

MCMC using Hamiltonian dynamics

RM Neal - arxiv preprint arxiv:1206.1901, 2012 - arxiv.org
Hamiltonian dynamics can be used to produce distant proposals for the Metropolis
algorithm, thereby avoiding the slow exploration of the state space that results from the …