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Anirban Mondal
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Year
Bayesian uncertainty quantification for flows in heterogeneous porous media using reversible jump Markov chain Monte Carlo methods
A Mondal, Y Efendiev, B Mallick, A Datta-Gupta
Advances in Water Resources 33 (3), 241-256, 2010
742010
SARS-CoV-2 infection in health care workers: A retrospective analysis and model study
Y Bai, X Wang, Q Huang, H Wang, D Gurarie, M Ndeffo-Mbah, F Fan, P Fu, ...
MedRxiv, 2020
38*2020
Risk factors of SARS-CoV-2 infection in healthcare workers: a retrospective study of a nosocomial outbreak
X Wang, X Jiang, Q Huang, H Wang, D Gurarie, M Ndeffo-Mbah, F Fan, ...
Sleep medicine: X 2, 100028, 2020
272020
Bayesian uncertainty quantification for subsurface inversion using a multiscale hierarchical model
A Mondal, B Mallick, Y Efendiev, A Datta-Gupta
Technometrics 56 (3), 381-392, 2014
232014
Analyzing stochastic computer models: a review with opportunities
E Baker, P Barbillon, A Fadikar, RB Gramacy, R Herbei, D Higdon, ...
Statistical Science 37 (1), 64-89, 2022
21*2022
SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study
Q Huang, A Mondal, X Jiang, MA Horn, F Fan, P Fu, X Wang, H Zhao, ...
Royal Society Open Science 8 (3), 201895, 2021
112021
Computer model calibration based on image warping metrics: an application for sea ice deformation
Y Guan, C Sampson, JD Tucker, W Chang, A Mondal, M Haran, D Sulsky
Journal of Agricultural, Biological and Environmental Statistics 24 (3), 444-463, 2019
102019
Stratified random sampling for dependent inputs in Monte Carlo simulations from computer experiments
A Mondal, A Mandal
Journal of Statistical Planning and Inference 205, 269-282, 2020
82020
A new approach for fast evaluations of large portfolios of oil and gas fields
D Castiñeira, A Mondal, S Matringe
SPE Annual Technical Conference and Exhibition, 2014
72014
Computer model emulation with high-dimensional functional output in large-scale observing system uncertainty experiments
P Ma, A Mondal, BA Konomi, J Hobbs, JJ Song, EL Kang
Technometrics 64 (1), 65-79, 2022
62022
Spatial retrievals of atmospheric carbon dioxide from satellite observations
J Hobbs, M Katzfuss, D Zilber, J Brynjarsdóttir, A Mondal, V Berrocal
Remote Sensing 13 (4), 571, 2021
22021
History Matching Channelized Reservoirs Using Reversible Jump Markov Chain Monte Carlo Methods
J Xie, A Mondal, Y Efendiev, B Mallick, A Datta-Gupta
SPE Improved Oil Recovery Symposium, 2010
22010
Preconditioning Markov Chain Monte Carlo Method for Geomechanical Subsidence using multiscale method and machine learning technique
M Vasilyeva, A Tyrylgin, DL Brown, A Mondal
Journal of Computational and Applied Mathematics 392, 113420, 2021
12021
Bayesian uncertainty quantification for channelized reservoirs via reduced dimensional parameterization
A Mondal, J Wei
Mathematics 9 (9), 1067, 2021
12021
Individual-based modeling of COVID-19 transmission in college communities
Q Huang, M Ndeffo-Mbah, A Mondal, S Lee, D Gurarie
medRxiv, 2021
12021
A Two Stage Adaptive Metropolis Algorithm
A Mondal, K Yin, A Mandal
arXiv preprint arXiv:2101.00118, 2021
12021
A Parametric Approach to Unmixing Remote Sensing Crop Growth Signatures
C Lewis-Beck, A Mondal, Z Zhu, JJ Song, J Hobbs
Journal of Agricultural, Biological and Environmental Statistics 24 (3), 502-516, 2019
12019
Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems
A Mondal
Texas A & M University, 2012
12012
Bayesian Analysis of Rank Data with Covariates and Heterogeneous Rankers...................................................... Xinran Li, Dingdong Yi and Jun S. Liu 1 The …
M Oesting, K Strokorb, P Barbillon, A Fadikar, RB Gramacy, R Herbei, ...
Statistical Science [ISSN 0883-4237 (print); ISSN 2168-8745 (online)] 37 (1), 2022
2022
Bayesian Uncertainty Quantification of Local Volatility Model
K Yin, A Mondal
arXiv preprint arXiv:2105.10210, 2021
2021
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Articles 1–20