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Machine Learning Evolution Equations : Inverse Reconstruction from Simulated Data - Joseph L. Shomberg

Machine Learning Evolution Equations

Inverse Reconstruction from Simulated Data

By: Joseph L. Shomberg

Paperback | 22 March 2027

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How can we reconstruct the past from the present when evolution obscures the information we need? Machine Learning Evolution Equations connects the analysis of partial differential equations with numerical simulation and machine learning to investigate this question. Through models of diffusion, phase separation, fluid flow, and wave propagation, the book develops methods for learning inverse reconstructions from simulated data. Reconstruction accuracy, physical consistency, and statistical validation provide a framework for assessing what these models can recover. Written for graduate students and researchers, it links rigorous mathematics with reproducible computational experiments.

You Can Find This Book In

Non-FictionMathematicsCalculus & Mathematical AnalysisDifferential Calculus & EquationsEngineering & TechnologyIndustrial Chemistry & Manufacturing TechnologiesComputing & I.T.Computer Programming & Software DevelopmentAlgorithms & Data Structures

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