papers
Publications (3)
physics.ao-ph2024
Graph Convolutional Neural Networks as Surrogate Models for Climate Simulation
Kevin Potter, Carianne Martinez, Reina Pradhan +3
Many climate processes are characterized using large systems of nonlinear differential equations; this, along with the immense amount of data required to parameterize complex inter…
physics.comp-ph2021
A Tailored Convolutional Neural Network for Nonlinear Manifold Learning of Computational Physics Data using Unstructured Spatial Discretizations
John Tencer, Kevin Potter
We propose a nonlinear manifold learning technique based on deep convolutional autoencoders that is appropriate for model order reduction of physical systems in complex geometries.…
cs.CV2022
Feature anomaly detection system (FADS) for intelligent manufacturing
Anthony Garland, Kevin Potter, Matt Smith
Anomaly detection is important for industrial automation and part quality assurance, and while humans can easily detect anomalies in components given a few examples, designing a ge…