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Higher-Order LaSDI: Reduced Order Modeling with Multiple Time Derivatives
Robert Stephany, William Michael Anderson, Youngsoo Choi
Solving complex partial differential equations is vital in the physical sciences, but often requires computationally expensive numerical methods. Reduced-order models (ROMs) addres…
Sequential decoder training for improved latent space dynamics identification
William Anderson, Seung Whan Chung, Youngsoo Choi
Accurate numerical solutions of partial differential equations are essential in many scientific fields but often require computationally expensive solvers, motivating reduced-order…
mLaSDI: Multi-stage latent space dynamics identification
William Anderson, Seung Whan Chung, Robert Stephany +1
Accurately solving partial differential equations (PDEs) is essential across many scientific disciplines. However, high-fidelity solvers can be computationally prohibitive, motivat…
Defining Foundation Models for Computational Science: A Call for Clarity and Rigor
Youngsoo Choi, Siu Wun Cheung, Youngkyu Kim +9
The widespread success of foundation models in natural language processing and computer vision has inspired researchers to extend the concept to scientific machine learning and com…