P
Pritam Ranjan
Researcher at Indian Institute of Management Indore
Publications - 69
Citations - 1173
Pritam Ranjan is an academic researcher from Indian Institute of Management Indore. The author has contributed to research in topics: Gaussian process & Computer experiment. The author has an hindex of 14, co-authored 64 publications receiving 1038 citations. Previous affiliations of Pritam Ranjan include Simon Fraser University & Acadia University.
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Modeling an Augmented Lagrangian for Improved Blackbox Constrained Optimization
Robert B. Gramacy,Genetha Anne Gray,Sébastien Le Digabel,Herbert K. H. Lee,Pritam Ranjan,Garth N. Wells,Stefan M. Wild +6 more
TL;DR: In this paper, a combination of response surface modeling, expected improvement, and the augmented Lagrangian numerical optimization framework is proposed for constrained black-box optimization of hydrology problems.
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A Sequential Design Approach for Calibrating Dynamic Computer Simulators
TL;DR: In this paper, computer simulators are widely used to describe and explore complex physical processes, and the simulator outputs may come in various formats: scalar, multivariate, functional, time series, spatial tem...
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Determining the magnitude of true analytical error in geochemical analysis
TL;DR: In this article, the authors used replicate analyses of sub-samples of two different masses, and solving a system of three equations in three unknowns, to deduce and distinguish the actual analytical error from sub-sampling error.
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A New Tree-based Classifier for Satellite Images
Reshu Agarwal,Pritam Ranjan +1 more
TL;DR: In this paper, the authors proposed a new reliable multiclass-classifier for identifying class labels of a satellite image in remote sensing applications based on the flexible ensemble of regression trees model called Bayesian Additive Regression Trees (BART).
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A History Matching Approach for Calibrating Hydrological Models.
Natalia V. Bhattacharjee,Natalia V. Bhattacharjee,Pritam Ranjan,Abhyuday Mandal,Ernest W. Tollner +4 more
TL;DR: In this paper, a modified history matching approach was proposed for calibrating the time-series rainfall-runoff models with respect to real data collected from the state of Georgia, USA.