Troy Butler

761 total citations
45 papers, 500 citations indexed

About

Troy Butler is a scholar working on Statistics, Probability and Uncertainty, Artificial Intelligence and Atmospheric Science. According to data from OpenAlex, Troy Butler has authored 45 papers receiving a total of 500 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Statistics, Probability and Uncertainty, 9 papers in Artificial Intelligence and 9 papers in Atmospheric Science. Recurrent topics in Troy Butler's work include Probabilistic and Robust Engineering Design (23 papers), Advanced Multi-Objective Optimization Algorithms (8 papers) and Gaussian Processes and Bayesian Inference (8 papers). Troy Butler is often cited by papers focused on Probabilistic and Robust Engineering Design (23 papers), Advanced Multi-Objective Optimization Algorithms (8 papers) and Gaussian Processes and Bayesian Inference (8 papers). Troy Butler collaborates with scholars based in United States, Finland and Saudi Arabia. Troy Butler's co-authors include Clint Dawson, Timothy Wildey, Donald Estep, Talea Mayo, Ibrahim Hoteit, John Jakeman, Joannes J. Westerink, M. U. Altaf, Xiaodong Luo and Steven Mattis and has published in prestigious journals such as Water Resources Research, Journal of Computational Physics and Monthly Weather Review.

In The Last Decade

Troy Butler

41 papers receiving 469 citations

Peers

Troy Butler

SPU

OCEAN

CTM

Matthias Morzfeld United States

Maëlle Nodet France

Ronald D. Haynes Canada

Mohamed Jardak United States

Sicheng He United States

Alfredo Garbuno-Iñigo United States

Amos S. Lawless United Kingdom

Stefano Ubbiali Switzerland

V. P. Shutyaev Russia

Frank Kwasniok United Kingdom

Matthias Morzfeld United States

Troy Butler

80 ×0.4

SPU

158 ×1.3

158 ×1.6

30 ×0.3

OCEAN

43 ×0.5

CTM

Citations per year, relative to Troy Butler Troy Butler (= 1×) peers Matthias Morzfeld

Countries citing papers authored by Troy Butler

Since Specialization

Citations

This map shows the geographic impact of Troy Butler's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Troy Butler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Troy Butler more than expected).

Fields of papers citing papers by Troy Butler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Troy Butler. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Troy Butler. The network helps show where Troy Butler may publish in the future.

Co-authorship network of co-authors of Troy Butler

This figure shows the co-authorship network connecting the top 25 collaborators of Troy Butler. A scholar is included among the top collaborators of Troy Butler based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Troy Butler. Troy Butler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Hakula, Harri, et al.. (2025). A machine-learning enabled framework for quantifying uncertainties in parameters of computational models. Computers & Mathematics with Applications. 182. 184–212.

Butler, Troy, et al.. (2024). A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory. Society for Industrial and Applied Mathematics eBooks.

Butler, Troy, et al.. (2024). STABILITY AND CONVERGENCE OF SOLUTIONS TO STOCHASTIC INVERSE PROBLEMS USING APPROXIMATE PROBABILITY DENSITIES. International Journal for Uncertainty Quantification. 15(4). 21–51. 2 indexed citations

Butler, Troy, et al.. (2024). A Distributions-Based Approach for Data-Consistent Inversion. SIAM Journal on Scientific Computing. 46(5). A3124–A3150.

Butler, Troy, et al.. (2023). Parameter estimation with maximal updated densities. Computer Methods in Applied Mechanics and Engineering. 407. 115906–115906. 8 indexed citations

Estep, Donald, et al.. (2021). Adjoint Sensitivity Analysis for Uncertain Material Parameters in Frequency-Domain 3-D FEM. IEEE Transactions on Antennas and Propagation. 69(10). 6669–6679. 9 indexed citations

Estep, Donald, et al.. (2020). Adjoint-Based Accelerated Adaptive Refinement in Frequency Domain 3-D Finite Element Method Scattering Problems. IEEE Transactions on Antennas and Propagation. 69(2). 940–949. 17 indexed citations

Butler, Troy, John Jakeman, & Timothy Wildey. (2020). Optimal experimental design for prediction based on push-forward probability measures. Journal of Computational Physics. 416. 109518–109518. 7 indexed citations

Estep, Donald, et al.. (2020). A Posteriori Error Estimation and Adaptive Discretization Refinement Using Adjoint Methods in CEM: A Study With a 1-D Higher Order FEM Scattering Example. IEEE Transactions on Antennas and Propagation. 68(5). 3791–3806. 9 indexed citations

10.

Butler, Troy, et al.. (2020). Data-consistent inversion for stochastic input-to-output maps*. Inverse Problems. 36(8). 85015–85015. 8 indexed citations

11.

Mattis, Steven & Troy Butler. (2019). Enhancing piecewise‐defined surrogate response surfaces with adjoints on sets of unstructured samples to solve stochastic inverse problems. International Journal for Numerical Methods in Engineering. 119(10). 923–940. 1 indexed citations

12.

Butler, Troy & Timothy Wildey. (2018). UTILIZING ADJOINT-BASED ERROR ESTIMATES FOR SURROGATE MODELS TO ACCURATELY PREDICT PROBABILITIES OF EVENTS. International Journal for Uncertainty Quantification. 8(2). 143–159. 4 indexed citations

13.

Notaroš, Branislav M., et al.. (2018). Adjoint methods for uncertainty quantification in applied computational electromagnetics: FEM scattering examples. 1–2. 4 indexed citations

14.

Butler, Troy, et al.. (2017). A Measure-Theoretic Interpretation of Sample Based Numerical Integration with Applications to Inverse and Prediction Problems under Uncertainty. SIAM Journal on Scientific Computing. 39(5). A2072–A2098. 9 indexed citations

15.

Mattis, Steven, et al.. (2016). BET: Butler, Estep, Tavener Method v2.0.0. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations

16.

Butler, Troy, et al.. (2015). Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models. Advances in Water Resources. 78. 60–79. 19 indexed citations

17.

Butler, Troy, et al.. (2014). Quantifying uncertainty in material damage from vibrational data. Journal of Computational Physics. 283. 414–435. 4 indexed citations

18.

Butler, Troy, et al.. (2012). A Computational Measure Theoretic Approach to Inverse Sensitivity Problems II: A Posteriori Error Analysis. SIAM Journal on Numerical Analysis. 50(1). 22–45. 24 indexed citations

19.

Butler, Troy, et al.. (2011). A Measure-Theoretic Computational Method for Inverse Sensitivity Problems I: Method and Analysis. SIAM Journal on Numerical Analysis. 49(5). 1836–1859. 32 indexed citations

20.

Butler, Troy, Clint Dawson, & Timothy Wildey. (2011). A Posteriori Error Analysis of Stochastic Differential Equations Using Polynomial Chaos Expansions. SIAM Journal on Scientific Computing. 33(3). 1267–1291. 28 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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