M. Parno

发表

An introduction to sampling via measure transport

Y. Marzouk, T. Moselhy, M. Parno, 2016, 1602.05023.

Applicability of surrogates to improve efficiency of particle swarm optimization for simulation-based problems

Thomas Hemker, Matthew Parno, Katie Fowler, 2012 .

Transport Map Accelerated Markov Chain Monte Carlo

Youssef Marzouk, Matthew Parno, Y. Marzouk, 2014, SIAM/ASA J. Uncertain. Quantification.

Computationally efficient inference for multiphase flow using the Ensemble Kalman Filter.

Youssef M. Marzouk, Sean Andrew McKenna, Bart Gustaaf van Bloemen Waanders, 2010 .

Bayesian data assimilation for stochastic multiscale models of transport in porous media.

Y. Marzouk, B. V. B. Waanders, M. Parno, 2011 .

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Michael W. Dusenberry, Benjamin D. Trump, Long T. Le, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Transport Map Accelerated Markov Chain Monte Carlo

Y. Marzouk, M. Parno, 2014, SIAM/ASA J. Uncertain. Quantification.

Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs

M. Parno, Bohan Zhou, 2022, ArXiv.

Integrated Mathematical Analysis of Agricultural Systems and Associated Water Use Impacts Using Coupled Software Frameworks

M. Parno, R. Hanson, K. Fowler, 2016 .

An Example of Agricultural Water Management with MODFLOW-FMP 2 and DAKOTA

M. Parno, K. Fowler, M. Farthing, 2014 .

The third Sandia fracture challenge: predictions of ductile fracture in additively manufactured metal

James W. Foulk, Steffen Brinckmann, Joseph E. Bishop, 2019, International Journal of Fracture.

Transport maps for accelerated Bayesian computation

Matthew Parno, M. Parno, 2015 .

hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty

Y. Marzouk, O. Ghattas, M. Parno, 2021, ACM Trans. Math. Softw..

A Multiscale Strategy for Bayesian Inference Using Transport Maps

Youssef M. Marzouk, Tarek A. El-Moselhy, Matthew D. Parno, 2015, SIAM/ASA J. Uncertain. Quantification.

Remote Measurement of Sea Ice Dynamics With Regularized Optimal Transport pdf

Matthew D. Parno, Brendan A. West, Taylor S. Hodgdon, 2019, Geophysical Research Letters.

Bayesian calibration of multi-level model with unobservable distributed response and application to miter gates

Mukesh K. Ramancha, Michael D. Todd, M. Parno, 2022, Mechanical Systems and Signal Processing.

COVID-19 infection data encode a dynamic reproduction number in response to policy decisions with secondary wave implications

Benjamin D. Trump, M. Parno, I. Linkov, 2020, Scientific Reports.

Framework for Particle Swarm Optimization with Surrogate Functions

Thomas Hemker, K. R. Fowler, Matthew Parno, 2009 .

Improved Workflow for Unsupervised Multiphase Image Segmentation

Matthew D. Parno, Brendan A. West, Taylor S. Hodgdon, 2017, Comput. Geosci..

Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs

M. Parno, Bohan Zhou, 2022, ArXiv.

Derivative-Free Optimization Via Evolutionary Algorithms Guiding Local Search

Genetha Anne Gray, Thomas Hemker, K. R. Fowler, 2011 .

Observations of Stress-Strain in Drifting Sea Ice at Floe Scale

J. Parno, M. Parno, C. Polashenski, 2021 .

Accounting for model form uncertainty in Bayesian calibration of linear dynamic systems

Mukesh K. Ramancha, M. Parno, J. Conte, 2022, Mechanical Systems and Signal Processing.

Improving discrete element simulations of sea ice break up: Applications to Nares Strait

M. Parno, C. Polashenski, D. O'Connor, 2021 .

ParticLS: Object-oriented software for discrete element methods and peridynamics

Brendan A. West, Andrew D. Davis, Nathanael J. Frisch, 2021, Computational Particle Mechanics.

FlakeOut: A Geometric Approach to Remove Wind-Blown Snow from Terrestrial Laser Scans

M. Parno, D. Perovich, C. Polashenski, 2022, 2202.00724.

Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait

M. Parno, C. Polashenski, D. O'Connor, 2021, Journal of Advances in Modeling Earth Systems.

Efficient and Exact Multimarginal Optimal Transport with Pairwise Costs

M. Parno, Bohan Zhou, 2022, J. Sci. Comput..

MUQ: The MIT Uncertainty Quantification Library

M. Parno, Andrew Davis, L. Seelinger, 2021, J. Open Source Softw..

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Michael W. Dusenberry, Benjamin D. Trump, Michael L. Mayo, 2022, Proceedings of the National Academy of Sciences of the United States of America.

UM-Bridge: Uncertainty quantification and modeling bridge

M. Parno, A. Reinarz, A. Davis, 2023, Journal of Open Source Software.

HIPPYLIB-MUQ: SCALABLE MARKOV CHAIN MONTE CARLO SAMPLING METHODS FOR LARGE-SCALE BAYESIAN INVERSE PROBLEMS GOVERNED BY PDES

O. Ghattas, M. Parno, N. Petra, 2021 .

A decision making framework with MODFLOW-FMP2 via optimization: Determining trade-offs in crop selection

Matthew W. Farthing, Kathleen R. Fowler, J. C. Chrispell, 2015, Environ. Model. Softw..

MParT: Monotone Parameterization Toolkit

Y. Marzouk, M. Parno, M. Brennan, 2022, Journal of Open Source Software.

A transport approach to sequential simulation-based inference

Y. Marzouk, M. Parno, Paul-Baptiste Rubio, 2023, ArXiv.

Munition penetration-depth prediction : SERDP SEED Project MR-2629

David M. Cole, Oliver-Denzil S. Taylor, Brendan A. West, 2017 .

MIT Open Access Articles A Multiscale Strategy for Bayesian Inference Using Transport Maps

T. Moselhy, M. Parno, Youssef Marzouk, 2022 .

The United States COVID-19 Forecast Hub dataset

Benjamin D. Trump, Julie S. Ivy, Sercan Ö. Arik, 2021, Scientific Data.