Tag: Hybrid Modeling

2 entries

Patient-Specific Hemodynamics via Hybrid Physics-Neural Surrogates

Biomedical Flow / Reduced-Order Model
Neural networks predict 0D reduced-order model parameters from geometry, cutting cardiovascular flow error by over half and running complex pulmonary cases in under 2 seconds on a laptop.
arXiv preprint (copyright held by authors) HemodynamicsReduced OrderDigital Twin

JAX-CFD

Differentiable Fluid Solver
Google Research's differentiable JAX-based fluid solver enabling end-to-end gradients for embedding neural networks into CFD time stepping.
Apache-2.0 JAXDifferentiable PhysicsCFD

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