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math.PR2021
Large deviation principle for occupation measures of stochastic generalized Burgers-Huxley equation
Ankit Kumar, Manil T. Mohan
The present work deals with the global solvability as well as asymptotic analysis of stochastic generalized Burgers-Huxley (SGBH) equation perturbed by space-time white noise in a…
stat.ME2021
Numerical Characterization of Support Recovery in Sparse Regression with Correlated Design
Ankit Kumar, Sharmodeep Bhattacharyya, Kristofer Bouchard
Sparse regression is frequently employed in diverse scientific settings as a feature selection method. A pervasive aspect of scientific data that hampers both feature selection and…
math.PR2021
Large deviation principle for occupation measures of two dimensional stochastic convective Brinkman-Forchheimer equations
Ankit Kumar, Manil T. Mohan
The present work is concerned about two-dimensional stochastic convective Brinkman-Forchheimer (2D SCBF) equations perturbed by a white noise (non degenerate) in smooth bounded dom…