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David Higdon
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- affiliation: Virginia Tech, Blacksburg, VA, USA
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2020 – today
- 2024
- [c7]Arindam Fadikar, Abby Stevens, Nicholson T. Collier, Kok Ben Toh, Olga Morozova, Anna Hotton, Jared Clark, David Higdon, Jonathan Ozik:
Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo. IPDPS (Workshops) 2024: 843-852 - 2023
- [j18]Annie Sauer, Robert B. Gramacy, David Higdon:
Active Learning for Deep Gaussian Process Surrogates. Technometrics 65(1): 4-18 (2023) - 2020
- [j17]Brian de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz:
Discovery of Physics From Data: Universal Laws and Discrepancies. Frontiers Artif. Intell. 3: 25 (2020)
2010 – 2019
- 2019
- [j16]Srinivasan Venkatramanan
, Jiangzhuo Chen, Arindam Fadikar
Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints. PLoS Comput. Biol. 15(9) (2019) - [i1]Brian de Silva, David M. Higdon, Steven L. Brunton, J. Nathan Kutz:
Discovery of Physics from Data: Universal Laws and Discrepancy Models. CoRR abs/1906.07906 (2019) - 2018
- [j15]Bianica Pires, Gizem Korkmaz, Katherine B. Ensor
Estimating individualized exposure impacts from ambient ozone levels: A synthetic information approach. Environ. Model. Softw. 103: 146-157 (2018) - [j14]Arindam Fadikar
Calibrating a Stochastic, Agent-Based Model Using Quantile-Based Emulation. SIAM/ASA J. Uncertain. Quantification 6(4): 1685-1706 (2018) - 2017
- [j13]Carène Larmat
Joining statistics and geophysics for assessment and uncertainty quantification of three-dimensional seismic Earth models. Stat. Anal. Data Min. 10(5): 277-289 (2017) - [c6]Farzaneh Tabataba, Bryan L. Lewis, Milad Hosseinipour, Foroogh S. Tabataba, Srinivasan Venkatramanan, Jiangzhuo Chen, Dave Higdon, Madhav V. Marathe:
Epidemic Forecasting Framework Combining Agent-Based Models and Smart Beam Particle Filtering. ICDM 2017: 1099-1104 - [c5]Bianica Pires, Joshua Goldstein, Dave Higdon, Paul Sabin
A Bayesian simulation approach for supply chain synchronization. WSC 2017: 1571-1582 - 2016
- [j12]James R. Gattiker
Using a Gaussian Process as a Nonparametric Regression Model. Qual. Reliab. Eng. Int. 32(2): 673-680 (2016) - [j11]Matthew T. Pratola, David M. Higdon:
Bayesian Additive Regression Tree Calibration of Complex High-Dimensional Computer Models. Technometrics 58(2): 166-179 (2016) - [c4]Bianica Pires, Joshua Goldstein, David Higdon, Gizem Korkmaz, Sallie Keller, Stephanie Shipp
A Bayesian simulation approach for supply chain synchronization. WSC 2016: 3698-3699 - 2015
- [j10]Brian P. Weaver, Richard L. Warr
Visualizing discrepancies from nonlinear models and computer experiments. Stat. Anal. Data Min. 8(5-6): 274-286 (2015) - 2014
- [c3]Humberto C. Godinez, Earl Lawrence
Specification of the Ionosphere-Thermosphere Using the Ensemble Kalman Filter. DyDESS 2014: 274-283 - 2013
- [j9]Tracy Holsclaw, Bruno Sansó, Herbert K. H. Lee, Katrin Heitmann, Salman Habib, David Higdon, Ujjaini Alam:
Gaussian Process Modeling of Derivative Curves. Technometrics 55(1): 57-67 (2013) - [j8]Curtis B. Storlie, Michael Fugate, David M. Higdon, Aparna V. Huzurbazar, Elizabeth G. Francois, Douglas C. McHugh:
Methods for Characterizing and Comparing Populations of Shock Wave Curves. Technometrics 55(4): 436-449 (2013) - [j7]David Higdon, James R. Gattiker
Computer Model Calibration Using the Ensemble Kalman Filter. Technometrics 55(4): 488-500 (2013) - 2012
- [j6]Tan Bui-Thanh
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. 34(6) (2012)
2000 – 2009
- 2006
- [j5]Crystal Linkletter, Derek Bingham, Nicolas W. Hengartner
Variable Selection for Gaussian Process Models in Computer Experiments. Technometrics 48(4): 478-490 (2006) - [c2]James R. Gattiker
Analysis of Multi-domain Complex Simulation Studies. ICCSA (3) 2006: 1153-1162 - 2004
- [j4]Dave Higdon, Marc C. Kennedy
Combining Field Data and Computer Simulations for Calibration and Prediction. SIAM J. Sci. Comput. 26(2): 448-466 (2004) - 2002
- [j3]Herbert K. H. Lee, David M. Higdon, Zhuoxin Bi, Marco A. R. Ferreira, Mike West:
Markov Random Field Models for High-Dimensional Parameters in Simulations of Fluid Flow in Porous Media. Technometrics 44(3): 230-241 (2002) - [j2]Dave Higdon, Herbert K. H. Lee, Zhuoxin Bi:
A Bayesian approach to characterizing uncertainty in inverse problems using coarse and fine-scale information. IEEE Trans. Signal Process. 50(2): 389-399 (2002)
1990 – 1999
- 1999
- [c1]David M. Higdon, James E. Bowsher:
Bayesian inference and Markov chain Monte Carlo in imaging. Image Processing 1999 - 1997
- [j1]David M. Higdon, James E. Bowsher, Valen E. Johnson, Timothy G. Turkington, David R. Gilland, Ronald J. Jaszczak:
Fully Bayesian Estimation of Gibbs Hyperparameters for Emission Computed Tomography Data. IEEE Trans. Medical Imaging 16(5): 516-526 (1997)
Coauthor Index
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