Continuous methods

Building on recent work using neural fields as representation for PDE solving, we investigate how to incorporate symmetries that often occur in physical data into a framework for continuous PDE solving by using Equivariant Neural Fields. We obtain …

Performant Convolutional Neural Network (CNN) architectures must be tailored to specific tasks in order to consider the length, resolution, and dimensionality of the input data. In this work, we tackle the need for problem-specific CNN architectures. …