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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 276–300 of 347 papers

TitleStatusHype
Operator learning with PCA-Net: upper and lower complexity bounds—0
Multiscale Attention via Wavelet Neural Operators for Vision Transformers—0
Solving High-Dimensional Inverse Problems with Auxiliary Uncertainty via Operator Learning with Limited Data—0
LNO: Laplace Neural Operator for Solving Differential Equations—0
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEsCode0
ViTO: Vision Transformer-Operator—0
Super-Resolution Neural OperatorCode0
Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential EquationsCode0
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks—0
Variational Autoencoding Neural Operators—0
Fourier-RNNs for Modelling Noisy Physics Data—0
Physics informed WNO—0
Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equationsCode0
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning—0
Randomized prior wavelet neural operator for uncertainty quantification—0
An Enhanced V-cycle MgNet Model for Operator Learning in Numerical Partial Differential Equations—0
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning—0
On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators—0
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs—0
Neural Inverse Operators for Solving PDE Inverse Problems—0
Forecasting subcritical cylinder wakes with Fourier Neural Operators—0
On the limits of neural network explainability via descramblingCode0
Improved generalization with deep neural operators for engineering systems: Path towards digital twin—0
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis—0
Bayesian Inversion with Neural Operator (BINO) for Modeling Subdiffusion: Forward and Inverse Problems—0
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