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math.OC2020
Probabilistic Gradients for Fast Calibration of Differential Equation Models
Jon Cockayne, Andrew B. Duncan
Calibration of large-scale differential equation models to observational or experimental data is a widespread challenge throughout applied sciences and engineering. A crucial bottl…
math.OC2020
Manifold Learning for Accelerating Coarse-Grained Optimization
Dmitry Pozharskiy, Noah J. Wichrowski, Andrew B. Duncan +2
Algorithms proposed for solving high-dimensional optimization problems with no derivative information frequently encounter the "curse of dimensionality," becoming ineffective as th…