Matthew Parno
Cited by
Cited by
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
Transport map accelerated markov chain monte carlo
MD Parno, YM Marzouk
SIAM/ASA Journal on Uncertainty Quantification 6 (2), 645-682, 2018
Sampling via measure transport: An introduction
Y Marzouk, T Moselhy, M Parno, A Spantini
Handbook of uncertainty quantification 1, 2, 2016
An introduction to sampling via measure transport
Y Marzouk, T Moselhy, M Parno, A Spantini
arXiv preprint arXiv:1602.05023, 2016
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, 5-61, 2019
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
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
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
Transport maps for accelerated Bayesian computation
MD Parno
Massachusetts Institute of Technology, 2015
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
High dimensional inference for the structural health monitoring of lock gates
M Parno, D O'Connor, M Smith
arXiv preprint arXiv:1812.05529, 2018
MUQ: The MIT uncertainty quantification library
M Parno, A Davis, L Seelinger
Journal of Open Source Software 6 (68), 3076, 2021
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
hIPPYlib-MUQ: A Bayesian inference software framework for integration of data with complex predictive models under uncertainty
KT Kim, U Villa, M Parno, Y Marzouk, O Ghattas, N Petra
ACM Transactions on Mathematical Software, 2023
Framework for particle swarm optimization with surrogate functions
MD Parno, KR Fowler, T Hemker
Darmstadt Technical University, Darmstadt, 2009
MIT uncertainty quantification (MUQ) library
M Parno, A Davis, P Conrad, YM Marzouk
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), 10875, 2021
ParticLS: Object-oriented software for discrete element methods and peridynamics
AD Davis, BA West, NJ Frisch, DT O’Connor, MD Parno
Computational Particle Mechanics, 1-13, 2021
Bonded discrete element simulations of sea ice with non‐local failure: Applications to Nares Strait
B West, D O’Connor, M Parno, M Krackow, C Polashenski
Journal of Advances in Modeling Earth Systems 14 (6), e2021MS002614, 2022
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
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