Stochastic projection based approach for gradient free physics informed learning

Understand

We propose a stochastic projection-based gradient free physics-informed neural network.

• The proposed approach, referred to as the stochastic projection based physics informed neural network (SP-PINN), blends upscaled stochastic projection theory with the recently proposed physics-informed neural network.
• This results in a framework that is robust and can solve problems involving complex solution domain and discontinuities.
• SP-PINN is a gradient-free approach which addresses the computational bottleneck associated with automatic differentiation in conventional PINN.