Finetuned physics foundation model generalizes zero-shot from few DNS runs to laboratory RTI data, matching experimental mixing growth rates and handling unseen stable stratification.
Morph: Pde foundation models with arbitrary data modality
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2026 2verdicts
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jNO introduces a unified JAX tracing system for data-driven and physics-informed neural operator training that compiles domains, residuals, losses, and diagnostics into one pipeline.
citing papers explorer
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Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence
Finetuned physics foundation model generalizes zero-shot from few DNS runs to laboratory RTI data, matching experimental mixing growth rates and handling unseen stable stratification.
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jNO: A JAX Library for Neural Operator and Foundation Model Training
jNO introduces a unified JAX tracing system for data-driven and physics-informed neural operator training that compiles domains, residuals, losses, and diagnostics into one pipeline.