Aug. 18, 2023, 3:28 a.m. | /u/ai_physics2023

Machine Learning

Recently, two interesting papers trying to reconcile the classical methods, specifically, finite difference method with physics informed neural networks have been published that are worth reading.

1. [Weight initialization algorithm for physics-informed neural networks using finite differences](
2. [Physics Informed Neural Network using Finite Difference Method](

These two papers can be considered to be harmonizing classical finite difference method and Physics-Informed Neural Networks (PINNs).

The first paper incorporates finite difference solution for improving PINNs training loss. The second one uses …

difference machinelearning networks neural networks numerical paper physics physics-informed reading

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