AFAICT this is a fancy word for parameter estimation from simulation-heavy communities. Distinct from calibration for prbabilistic predictions.
Closely related to AutoML, in that surrogate optimisation is a popular tool for such, and adaptive design of experiment.
Surrogate optimisation
Classic GP surrogate optimisation is a popular tool for model calibration, see Kennedy and OβHagan (2001) for a classic example. More recent: Plumlee (2017).
MMD
See Dellaporta et al. (2022) for the application of maximum mean discrepancy to the problem of model calibration.
References
Bayarri, M. J., D. Walsh, J. O. Berger, J. Cafeo, G. Garcia-Donato, F. Liu, J. Palomo, R. J. Parthasarathy, R. Paulo, and J. Sacks. 2007. βComputer Model Validation with Functional Output.β The Annals of Statistics 35 (5): 1874β1906.
Bayarri, Maria J, James O Berger, Rui Paulo, Jerry Sacks, John A Cafeo, James Cavendish, Chin-Hsu Lin, and Jian Tu. 2007. βA Framework for Validation of Computer Models.β Technometrics 49 (2): 138β54.
Cockayne, Jon, and Andrew B. Duncan. 2020. βProbabilistic Gradients for Fast Calibration of Differential Equation Models,β September.
Dellaporta, Charita, Jeremias Knoblauch, Theodoros Damoulas, and FranΓ§ois-Xavier Briol. 2022. βRobust Bayesian Inference for Simulator-Based Models via the MMD Posterior Bootstrap.β arXiv:2202.04744 [Cs, Stat], February.
Doherty, John. 2015. Calibration and uncertainty analysis for complex environmental models.
Dunbar, Oliver R. A., Andrew B. Duncan, Andrew M. Stuart, and Marie-Therese Wolfram. 2022. βEnsemble Inference Methods for Models With Noisy and Expensive Likelihoods.β SIAM Journal on Applied Dynamical Systems 21 (2): 1539β72.
Higdon, Dave, James Gattiker, Brian Williams, and Maria Rightley. 2008. βComputer Model Calibration Using High-Dimensional Output.β Journal of the American Statistical Association 103 (482): 570β83.
Huang, Yingxiang, Wentao Li, Fima Macheret, Rodney A Gabriel, and Lucila Ohno-Machado. 2020. βA Tutorial on Calibration Measurements and Calibration Models for Clinical Prediction Models.β Journal of the American Medical Informatics Association : JAMIA 27 (4): 621β33.
Izmailov, Pavel, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, and Andrew Gordon Wilson. 2020. βSubspace Inference for Bayesian Deep Learning.β In Proceedings of The 35th Uncertainty in Artificial Intelligence Conference, 1169β79. PMLR.
Kennedy, Marc C., and Anthony OβHagan. 2001. βBayesian Calibration of Computer Models.β Journal of the Royal Statistical Society: Series B (Statistical Methodology) 63 (3): 425β64.
Koermer, Scott, Justin Loda, Aaron Noble, and Robert B. Gramacy. 2023. βActive Learning for Simulator Calibration.β arXiv.
Laloy, Eric, and Diederik Jacques. 2019. βEmulation of CPU-Demanding Reactive Transport Models: A Comparison of Gaussian Processes, Polynomial Chaos Expansion, and Deep Neural Networks.β Computational Geosciences 23 (5): 1193β1215.
Madan, Dilip B. 2014. βRecovering Statistical Theory in the Context of Model Calibrations.β Journal of Financial Econometrics 13 (2): nbu020.
McInerney, David, Mark Thyer, Dmitri Kavetski, Bree Bennett, Julien Lerat, Matthew Gibbs, and George Kuczera. 2018. βA Simplified Approach to Produce Probabilistic Hydrological Model Predictions.β Environmental Modelling & Software 109 (November): 306β14.
OβHagan, A. 1978. βCurve Fitting and Optimal Design for Prediction.β Journal of the Royal Statistical Society: Series B (Methodological) 40 (1): 1β24.
Oakley, Jeremy E., and Benjamin D. Youngman. 2017. βCalibration of Stochastic Computer Simulators Using Likelihood Emulation.β Technometrics 59 (1): 80β92.
Perdikaris, Paris, and George Em Karniadakis. 2016. βModel inversion via multi-fidelity Bayesian optimization: a new paradigm for parameter estimation in haemodynamics, and beyond.β Journal of the Royal Society, Interface 13 (118): 20151107.
Pleiss, Geoff, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q. Weinberger. 2017. βOn Fairness and Calibration.β In Advances In Neural Information Processing Systems.
Plumlee, Matthew. 2017. βBayesian Calibration of Inexact Computer Models.β Journal of the American Statistical Association 112 (519): 1274β85.
Regis, Rommel G., and Christine A. Shoemaker. 2013. βCombining Radial Basis Function Surrogates and Dynamic Coordinate Search in High-Dimensional Expensive Black-Box Optimization.β Engineering Optimization 45 (5): 529β55.
Sacks, Jerome, Susannah B. Schiller, and William J. Welch. 1989. βDesigns for Computer Experiments.β Technometrics 31 (1): 41β47.
Sacks, Jerome, William J. Welch, Toby J. Mitchell, and Henry P. Wynn. 1989. βDesign and Analysis of Computer Experiments.β Statistical Science 4 (4): 409β23.
Thiagarajan, Jayaraman J., Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, and Brian Spears. 2020. βDesigning Accurate Emulators for Scientific Processes Using Calibration-Driven Deep Models.β Nature Communications 11 (1): 5622.
Tonkin, Matthew, and John Doherty. 2009. βCalibration-Constrained Monte Carlo Analysis of Highly Parameterized Models Using Subspace Techniques.β Water Resources Research 45 (12).
No comments yet. Why not leave one?