Author

Steven L. Brunton

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#machine learning May 2026

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling

In this selective-decoding experiment, AeroJEPA substantially outperforms the evaluated direct-regression surrogates while avoiding predictions over the remainder of the aircraft, and shows how predictive representations can support aerodynamic analysis with or without full-field reconstruction.

Francisco Giral, A. Vishwasrao, Andrea Arroyo Ramo et al. · arXiv.org · 1 citation

Review Jul 2026

An Introduction to Sparse Identification of Nonlinear Dynamics for Engineering Applications

Many engineering problems involve phenomena whose governing equations are poorly characterized or only partially known. Surrogate modeling techniques such as neural networks can capture the behavior of these systems, but they typically demand large training datasets that are difficult to obtain in engineering contexts...

Yao Li, Ana Larrañaga, Steven L. Brunton et al. · arXiv.org · 0 citations