Justin Goodwin — accepted AI-conference papers

2025

Bridging Equivariant GNNs and Spherical CNNs for Structured Physical Domains

Colin Kohler, Purvik Patel, Nathan Vaska, Justin Goodwin, Matthew C. Jones, Robert Platt +2

NeurIPS 2025poster

Many modeling tasks from disparate domains can be framed the same way, computing spherical signals from geometric inputs, for example, computing the radar response of different objects or navigating through an environment. This paper introduces G2Sphere, a general method for mapping object geometrie…

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2025

Reducing the Sensitivity of Neural Physics Simulators to Mesh Topology via Pretraining

Nathan Vaska, Justin Goodwin, Robin Walters, Rajmonda Sulo Caceres

ICASSP 2025accepted

Meshes are used to represent complex objects in high fidelity physics simulators across a variety of domains, such as radar sensing and aerodynamics. There is growing interest in using neural networks to accelerate physics simulations, and also a growing body of work on applying neural networks dire…

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