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CARS: a centerline-anchored attention surrogate for coronary blood flow on skeleton-generated lumen geometries
Reza Akbarian Bafghi, Sukirt Thakur, Maziar Raissi
When the parameter of a PDE surrogate is the flow domain itself, the key/value set of an attention model must encode that domain. We present CARS (Coronary Artery Rapid Surrogate),…
Are Learned Vascular Tree Generators Better Than Conditional Resampling?
Reza Akbarian Bafghi, Sukirt Thakur, Maziar Raissi
Fidelity scores compare generated vascular trees with held-out real trees, so by themselves they cannot detect reuse of training data. A training-free conditional resampler shows t…
Deep LPPLS: Forecasting of temporal critical points in natural, engineering and financial systems
Joshua Nielsen, Didier Sornette, Maziar Raissi
The Log-Periodic Power Law Singularity (LPPLS) model offers a general framework for capturing dynamics and predicting transition points in diverse natural and social systems. In th…
PINNs-TF2: Fast and User-Friendly Physics-Informed Neural Networks in TensorFlow V2
Reza Akbarian Bafghi, Maziar Raissi
Physics-informed neural networks (PINNs) have gained prominence for their capability to tackle supervised learning tasks that conform to physical laws, notably nonlinear partial di…
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data
Maziar Raissi, Alireza Yazdani, George Em Karniadakis
We present hidden fluid mechanics (HFM), a physics informed deep learning framework capable of encoding an important class of physical laws governing fluid motions, namely the Navi…