3 papers
math.NA2026
Hybrid Joint-Selective Optimization: Reduced-Space Levenberg-Marquardt Refinement of Low-Dimensional Parameters of Interest
Muhammad Luthfi Shahab, Gabriella Alfa Indahsari, Imam Mukhlash +1
This paper introduces a hybrid joint-selective optimization (HJSO) framework for large-scale numerical problems in which a small subset of trainable quantities is of primary intere…
math.NA2026
Do physics-informed neural networks (PINNs) need to be deep? Shallow PINNs using the Levenberg-Marquardt algorithm
Muhammad Luthfi Shahab, Imam Mukhlash, Hadi Susanto
This work investigates shallow physics-informed neural networks (PINNs) for solving forward and inverse problems governed by nonlinear partial differential equations (PDEs). By for…
math.AP2023
A Deep-Genetic Algorithm (Deep-GA) Approach for High-Dimensional Nonlinear Parabolic Partial Differential Equations
Endah Rokhmati Merdika Putri, Muhammad Luthfi Shahab, Mohammad Iqbal +4
We propose a new method, called a deep-genetic algorithm (deep-GA), to accelerate the performance of the so-called deep-BSDE method, which is a deep learning algorithm to solve hig…