Numerical Analysis of Deep Learning Methods for the Allen-Cahn and Cahn-Hilliard Models

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dc.contributor.authorSingh, Anjali
dc.date.accessioned2026-07-31T10:55:47Z
dc.date.issued2026
dc.descriptionSinha, Rajen Kumar
dc.description.abstractUNDER EMBARGO
dc.identifier.otherROLL NO.196123101
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/3524
dc.language.isoen
dc.relation.ispartofseriesTH-4022
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectAllen-Cahn Equations
dc.subjectCahn-Hilliard Equations
dc.subjectMolecular Beam Epitaxy Equation
dc.subjectPhysics-Informed Neural Networks (PINNs)
dc.subjectOperator-Splitting Technique
dc.subjectMetropolis-Hastings-based Sampling
dc.subjectTemporal Domain Decomposition
dc.subjectTransfer Learning
dc.subjectTime-Stacked Training
dc.subjectError Estimate
dc.titleNumerical Analysis of Deep Learning Methods for the Allen-Cahn and Cahn-Hilliard Models
dc.typeThesis

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