Two-Phase Optimization for PINN Training

Published 11 Sep 2024 in math.OC | (2409.07296v1)

Abstract: This work presents an algorithm for training Neural Networks where the loss function can be decomposed into two non-negative terms to be minimized. The proposed method is an adaptation of Inexact Restoration algorithms, constituting a two-phase method that imposes descent conditions. Some performance tests are carried out in PINN training.

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Dimary Moreno López

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