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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 251–275 of 347 papers

TitleStatusHype
Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach—0
Operator Learning for Robust Stabilization of Linear Markov-Jumping Hyperbolic PDEs—0
U-WNO:U-Net-enhanced Wavelet Neural Operator for fetal head segmentation—0
Operator-learning-inspired Modeling of Neural Ordinary Differential Equations—0
Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods—0
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective—0
Operator learning regularization for macroscopic permeability prediction in dual-scale flow problem—0
An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning—0
A novel data generation scheme for surrogate modelling with deep operator networks—0
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis—0
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification—0
Operator learning with PCA-Net: upper and lower complexity bounds—0
opPINN: Physics-Informed Neural Network with operator learning to approximate solutions to the Fokker-Planck-Landau equation—0
Optimal deep learning of holomorphic operators between Banach spaces—0
Optimization for Neural Operators can Benefit from Width—0
Orthogonal greedy algorithm for linear operator learning with shallow neural network—0
An Enhanced V-cycle MgNet Model for Operator Learning in Numerical Partial Differential Equations—0
Parametric Learning of Time-Advancement Operators for Unstable Flame Evolution—0
Analysis Operator Learning and Its Application to Image Reconstruction—0
Physics and geometry informed neural operator network with application to acoustic scattering—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems—0
Koopman operator learning using invertible neural networks—0
Physics-Informed Latent Neural Operator for Real-time Predictions of Complex Physical Systems—0
Physics-informed Multiple-Input Operators for efficient dynamic response prediction of structures—0
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