Navier-Stokes

Navier Stokes Dataset of Isotropic Turbulence in a periodic box The dataset for tensor-to-tensor or trajectory-to-trajectory neural operators, generated from Navier-Stokes equations to model the isotropic turbulence [1] such that the spectra satisfy the inverse cascade discovered by A.N. Kolmogorov [2]. [1]: McWilliams

Papers using Navier-Stokes (8)

Size is Not the Solution: Deformable Convolutions for Effective Physics Aware Deep Learning2026KD-PINN: Knowledge-Distilled PINNs for ultra-low-latency real-time neural PDE solvers2025Deep Neural ODE Operator Networks for PDEs2025A Residual Guided strategy with Generative Adversarial Networks in training Physics-Informed Transformer Networks2025Embedding Trust at Scale: Physics-Aware Neural Watermarking for Secure and Verifiable Data Pipelines2025A Comparison of Mesh-Free Differentiable Programming and Data-Driven Strategies for Optimal Control under PDE Constraints2023 · 8 citesPARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling2024 · 3 citesNeural Integral Equations2022 · 2 cites