Fine-tuning neural PDE operators to regime endpoints reveals a physical direction in weight space that CCM uses to compose accurate merged models for new or extrapolated regimes from metadata or short prefixes.
Deep transfer operator learning for partial differential equations under conditional shift.Nature Machine Intelligence, 4(12):1155–1164
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Multimodal neural operators predict full-field brain displacement from MRE data with high accuracy and fast inference by fusing volumetric imaging, demographics, and acquisition parameters.
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Discovering Physical Directions in Weight Space: Composing Neural PDE Experts
Fine-tuning neural PDE operators to regime endpoints reveals a physical direction in weight space that CCM uses to compose accurate merged models for new or extrapolated regimes from metadata or short prefixes.
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Multimodal Neural Operators for Real-Time Biomechanical Modelling of Traumatic Brain Injury
Multimodal neural operators predict full-field brain displacement from MRE data with high accuracy and fast inference by fusing volumetric imaging, demographics, and acquisition parameters.