DynaSolver neural operator predicts autoregressive 4D flow with dynamic boundaries
DynaSolver conditions on boundary evolution and flow history to predict unsteady flows induced by moving boundaries in computational fluid dynamics.
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Stories tagged #neural-operators
Modest TFNO tuning beats published Well neural-operator baselines
With one input timestep and the same 12-hour limit, tuned TFNO lowers VRMSE on 15 of 17 tasks.
ZENO learns nonlinear filters with Zakai equation neural operators
The operator is trained with a physics-informed Zakai loss and used inside EM for state inference and SDE parameter learning.
PUN neural operator plans under control noise in unseen geometries
On a 4D replanning benchmark it reports 95-100% success across four noise levels and the lowest runtime among compared planners.
Neural Harmonic Measure Operator
NHMO learns a geometry-only kernel that solves variable-shape elliptic PDEs without retraining.
Learning Physics from an Imperfect Ancestor
A three-stage method uses an imperfect neural operator to steer PINNs into the correct PDE basin.
Local gradient neural operator
Researchers propose LGNO, a lightweight interpretable neural operator using learnable local stencils, matching global-operator accuracy on PDE benchmarks with fewer parameters.
🔬“We have foundation models for language, not for physics” — Anima Anandkumar, Bren Professor of Computing
Caltech professor Anima Anandkumar discusses Neural Operators and FourCastNet for physics modeling, arguing inductive biases beat pure token scaling.
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