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cs.LG2026
An Introduction to Sparse Identification of Nonlinear Dynamics for Engineering Applications
Yao Cheng Li, Ana Larrañaga, Steven L. Brunton +1
Many engineering problems involve phenomena whose governing equations are poorly characterized or only partially known. Surrogate modeling techniques such as neural networks can ca…
cs.LG2026
How Low Can You Go? Active Learning for Sparse Model Discovery in the Ultra-Low-Data Limit
Ana Larrañaga, Urban Fasel, Steven L. Brunton
Identifying the governing equations of complex dynamical systems remains a fundamental challenge across science and engineering. While early approaches relied on empirical data and…
cs.LG2026
AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling
Francisco Giral, Abhijeet Vishwasrao, Andrea Arroyo Ramo +8
High-fidelity CFD is essential for aerodynamic design, but repeated simulations are computationally expensive, motivating surrogate models for rapid evaluation across geometries an…