David Higdon

Affiliations:
  • Virginia Tech, Blacksburg, VA, USA


According to our database1, David Higdon authored at least 26 papers between 1997 and 2024.

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Bibliography

2024
Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

2023
Active Learning for Deep Gaussian Process Surrogates.
Technometrics, January, 2023

2020
Discovery of Physics From Data: Universal Laws and Discrepancies.
Frontiers Artif. Intell., 2020

2019
Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints.
PLoS Comput. Biol., 2019

Discovery of Physics from Data: Universal Laws and Discrepancy Models.
CoRR, 2019

2018
Calibrating a Stochastic, Agent-Based Model Using Quantile-Based Emulation.
SIAM/ASA J. Uncertain. Quantification, 2018

Estimating individualized exposure impacts from ambient ozone levels: A synthetic information approach.
Environ. Model. Softw., 2018

2017
Joining statistics and geophysics for assessment and uncertainty quantification of three-dimensional seismic Earth models.
Stat. Anal. Data Min., 2017

A Bayesian simulation approach for supply chain synchronization.
Proceedings of the 2017 Winter Simulation Conference, 2017

Epidemic Forecasting Framework Combining Agent-Based Models and Smart Beam Particle Filtering.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
Bayesian Additive Regression Tree Calibration of Complex High-Dimensional Computer Models.
Technometrics, 2016

Using a Gaussian Process as a Nonparametric Regression Model.
Qual. Reliab. Eng. Int., 2016

A Bayesian simulation approach for supply chain synchronization.
Proceedings of the Winter Simulation Conference, 2016

2015
Visualizing discrepancies from nonlinear models and computer experiments.
Stat. Anal. Data Min., 2015

2014
Specification of the Ionosphere-Thermosphere Using the Ensemble Kalman Filter.
Proceedings of the Dynamic Data-Driven Environmental Systems Science, 2014

2013
Methods for Characterizing and Comparing Populations of Shock Wave Curves.
Technometrics, 2013

Gaussian Process Modeling of Derivative Curves.
Technometrics, 2013

Computer Model Calibration Using the Ensemble Kalman Filter.
Technometrics, 2013

2012
Adaptive Hessian-Based Nonstationary Gaussian Process Response Surface Method for Probability Density Approximation with Application to Bayesian Solution of Large-Scale Inverse Problems.
SIAM J. Sci. Comput., 2012

2006
Variable Selection for Gaussian Process Models in Computer Experiments.
Technometrics, 2006

Analysis of Multi-domain Complex Simulation Studies.
Proceedings of the Computational Science and Its Applications, 2006

2004
Combining Field Data and Computer Simulations for Calibration and Prediction.
SIAM J. Sci. Comput., 2004

2002
A Bayesian approach to characterizing uncertainty in inverse problems using coarse and fine-scale information.
IEEE Trans. Signal Process., 2002

Markov Random Field Models for High-Dimensional Parameters in Simulations of Fluid Flow in Porous Media.
Technometrics, 2002

1999
Bayesian inference and Markov chain Monte Carlo in imaging.
Proceedings of the Medical Imaging 1999: Image Processing, 1999

1997
Fully Bayesian Estimation of Gibbs Hyperparameters for Emission Computed Tomography Data.
IEEE Trans. Medical Imaging, 1997


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