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Matthew Parno
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Transport map accelerated markov chain monte carlo
MD Parno, YM Marzouk
SIAM/ASA Journal on Uncertainty Quantification 6 (2), 645-682, 2018
1382018
Sampling via measure transport: An introduction
Y Marzouk, T Moselhy, M Parno, A Spantini
Handbook of uncertainty quantification 1, 2, 2016
1062016
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, AJC Rivadeneira, ...
Medrxiv, 2021
682021
An introduction to sampling via measure transport
Y Marzouk, T Moselhy, M Parno, A Spantini
arXiv preprint arXiv:1602.05023, 2016
672016
The third Sandia Fracture Challenge: predictions of ductile fracture in additively manufactured metal
SLB Kramer, A Jones, A Mostafa, B Ravaji, T Tancogne-Dejean, CC Roth, ...
International Journal of Fracture 218 (1), 5-61, 2019
602019
Applicability of surrogates to improve efficiency of particle swarm optimization for simulation-based problems
MD Parno, T Hemker, KR Fowler
Engineering optimization 44 (5), 521-535, 2012
432012
A multiscale strategy for Bayesian inference using transport maps
M Parno, T Moselhy, Y Marzouk
SIAM/ASA Journal on Uncertainty Quantification 4 (1), 1160-1190, 2016
312016
A decision making framework with MODFLOW-FMP2 via optimization: Determining trade-offs in crop selection
KR Fowler, EW Jenkins, C Ostrove, JC Chrispell, MW Farthing, M Parno
Environmental Modelling & Software 69, 280-291, 2015
302015
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ...
Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022
242022
Transport maps for accelerated Bayesian computation
MD Parno
Massachusetts Institute of Technology, 2015
212015
Derivative-free optimization via evolutionary algorithms guiding local search
JD Griffin, KR Fowler, GA Gray, T Hemker, MD Parno
Sandia National Laboratories, Albuquerque, NM, Tech. Rep. SAND2010-3023J, 2010
152010
Framework for particle swarm optimization with surrogate functions
MD Parno, KR Fowler, T Hemker
Darmstadt Technical University, Darmstadt, 2009
132009
High dimensional inference for the structural health monitoring of lock gates
M Parno, D O'Connor, M Smith
arXiv preprint arXiv:1812.05529, 2018
122018
MIT uncertainty quantification (MUQ) library
M Parno, A Davis, P Conrad, YM Marzouk
92014
A probabilistic optimal sensor design approach for structural health monitoring using risk-weighted f-divergence
Y Yang, M Chadha, Z Hu, MA Vega, MD Parno, MD Todd
Mechanical Systems and Signal Processing 161, 107920, 2021
82021
COVID-19 infection data encode a dynamic reproduction number in response to policy decisions with secondary wave implications
MA Rowland, TM Swannack, ML Mayo, M Parno, M Farthing, I Dettwiller, ...
Scientific reports 11 (1), 1-7, 2021
62021
MUQ: The MIT uncertainty quantification library
M Parno, A Davis, L Seelinger
Journal of Open Source Software 6 (68), 3076, 2021
52021
Remote measurement of sea ice dynamics with regularized optimal transport
MD Parno, BA West, AJ Song, TS Hodgdon, DT O'Connor
Geophysical Research Letters 46 (10), 5341-5350, 2019
52019
MIT Uncertainty Quantification (MUQ) Library, 2014
M Parno, A Davis, P Conrad, Y Marzouk
5
Accounting for model form uncertainty in Bayesian calibration of linear dynamic systems
MK Ramancha, JP Conte, MD Parno
Mechanical Systems and Signal Processing 171, 108871, 2022
32022
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