Inferring physical fields in coupled systems with unknown parameters from incomplete observations using physics-constrained attentive neural operators
cs.LG, cs.NA, math.NA
Submitted: 2026-10-05
Updated: 2026-10-05
Sources
- A Simple but Efficient Transformer-Based Physics-Informed Neural Network for Incompressible Navier--Stokes Equations
- An Efficient Wavelet-based Physics Informed Residual Neural Networks for Flow Field Reconstruction with Extremely Sparse Data
- Fourier Neural Operator for Parametric Partial Differential Equations
- Muon is Scalable for LLM Training
- Distributed physics-informed neural networks via domain decomposition for fast flow reconstruction
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