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cs.LG2025
Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling
Haley Rosso, Lars Ruthotto, Khachik Sargsyan
Continuous-time deep learning models, such as neural ordinary differential equations (ODEs), offer a promising framework for surrogate modeling of complex physical systems. A centr…
physics.ao-ph2025★ 1 cited
Improving the quasi-biennial oscillation via a surrogate-accelerated multi-objective optimization
Luis Damiano, Walter M. Hannah, Chih-Chieh Chen +4
Simulating the QBO remains a formidable challenge partly due to uncertainties in representing convectively generated gravity waves. We develop an end-to-end uncertainty quantificat…