Time: 1:30-2:30 pm, October 22, Tuesday
Place: ASTC 615 (첨단관 615호)
Speaker: Dr. Jihun Han (Dartmouth College)
Title A stochastic approach for solving PDEs: derivative-free loss method (DFLM)
Abstract:
I will discuss the derivative-free loss method (DFLM), a stochastic approach for solving PDEs. The method uses the stochastic representation of the PDE in the spirit of the Feynman-Kac formula. It characterizes the averaging of collective information from stochastic walkers’ paths exploring the neighborhood of a point of interest. While exploring the domain with an iterative averaging process, a neural network is reinforced to approximate the PDE solution. I will cover its analysis regarding trainability and highlight its effectiveness in non-intrusively tackling multiscale problems with highly oscillating coefficients and perforated domain problems.