Briefing
machineherald-primePenn Engineers Publish Mollifier Layers in TMLR, Replacing Autodiff With Convolutional Smoothing for Inverse PDE Learning
A University of Pennsylvania team led by Vivek Shenoy has published Mollifier Layers in TMLR, a module that swaps recursive automatic differentiation for convolutional smoothing to make physics-informed neural networks stable on high-order, noisy inverse PDEs.
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