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Ben Mansour Dia
Researcher at King Fahd University of Petroleum and Minerals
Publications - 22
Citations - 231
Ben Mansour Dia is an academic researcher from King Fahd University of Petroleum and Minerals. The author has contributed to research in topics: Monte Carlo method & Laplace's method. The author has an hindex of 6, co-authored 18 publications receiving 111 citations. Previous affiliations of Ben Mansour Dia include King Abdullah University of Science and Technology & University of the Sciences.
Papers
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Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain
TL;DR: This work presents a computationally efficient method for optimal Bayesian experimental design that introduces importance sampling based on the Laplace method to the inner loop and derives the optimal values for the method parameters in which the average computational cost is minimized for a specified error tolerance.
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Multilevel double loop Monte Carlo and stochastic collocation methods with importance sampling for Bayesian optimal experimental design
TL;DR: In this article, a multilevel Double Loop Monte Carlo (MLDLMC) is proposed to estimate the expected information gain for Bayesian inference of the fiber orientation in composite laminate materials from an electrical impedance tomography experiment.
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Nesterov-aided Stochastic Gradient Methods using Laplace Approximation for Bayesian Design Optimization
TL;DR: In this article, the authors use the stochastic gradient descent and its accelerated counterpart, which employs Nesterov's method, to solve the optimization problem in optimal experimental design (OED).
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Optimal control analysis of a COVID-19 and tuberculosis co-dynamics model
Mouhamadou Samsidy Goudiaby,Lucien Diégane Gning,M.L. Diagne,Ben Mansour Dia,H. Rwezaura,Jean M. Tchuenche +5 more
TL;DR: In this paper , a mathematical model for the co-infection of COVID-19 and tuberculosis is proposed to theoretically investigate the impact of control measures on their long-term dynamics.
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A novel NMR surface relaxivity measurements on rock cuttings for conventional and unconventional reservoirs
Lateef Owolabi Lawal,Abdulrauf Rasheed Adebayo,Mohamed Mahmoud,Ben Mansour Dia,Abdullah S. Sultan +4 more
TL;DR: In this paper, the NMR grain sizing method was proposed to estimate surface relaxivity of a given rock from only NMR measurements on rock cuttings, which is a simple and inexpensive approach that does not require supplementary measurements and offers an added advantage for characterizing thinly laminated formations.