Fourier Neural Operator parameterizes integral kernels in Fourier space to learn parametric PDE solution operators, delivering up to 1000x speedups and zero-shot super-resolution on turbulent Navier-Stokes flows.
Solving ill-posed inverse problems using iterative deep neural networks
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 5roles
background 1polarities
background 1representative citing papers
Graph Kernel Networks learn PDE solution operators that generalize across discretization methods and grid resolutions using graph-based kernel integration.
A framework of four reference images and sensitive metrics for tomography that reveals reconstruction discrepancies missed by global image quality measures.
RealLiFe optimizes multi-plane images with HSGD to deliver real-time light field reconstruction from sparse views, claiming 100x speedup over offline methods and 2 dB PSNR gain over online ones.
A new instrumentation lab for infrared medical imaging achieves approximately 25 mK measurement uncertainty and demonstrates feasibility for detecting sub-0.1 K surface temperature variations consistent with internal contrasts in tissue.
citing papers explorer
-
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator parameterizes integral kernels in Fourier space to learn parametric PDE solution operators, delivering up to 1000x speedups and zero-shot super-resolution on turbulent Navier-Stokes flows.
-
Neural Operator: Graph Kernel Network for Partial Differential Equations
Graph Kernel Networks learn PDE solution operators that generalize across discretization methods and grid resolutions using graph-based kernel integration.
-
Standardized Images and Evaluation Metrics for Tomography
A framework of four reference images and sensitive metrics for tomography that reveals reconstruction discrepancies missed by global image quality measures.
-
RealLiFe: Real-Time Light Field Reconstruction via Hierarchical Sparse Gradient Descent
RealLiFe optimizes multi-plane images with HSGD to deliver real-time light field reconstruction from sparse views, claiming 100x speedup over offline methods and 2 dB PSNR gain over online ones.
-
Development and Performance of an Instrumentation Laboratory for Infrared Medical Imaging
A new instrumentation lab for infrared medical imaging achieves approximately 25 mK measurement uncertainty and demonstrates feasibility for detecting sub-0.1 K surface temperature variations consistent with internal contrasts in tissue.