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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 301–325 of 347 papers

TitleStatusHype
NOMAD: Nonlinear Manifold Decoders for Operator Learning—0
Memory-efficient model-based deep learning with convergence and robustness guarantees—0
Transformer for Partial Differential Equations' Operator LearningCode1
Generic bounds on the approximation error for physics-informed (and) operator learning—0
Variable-Input Deep Operator Networks—0
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms—0
Wavelet neural operator: a neural operator for parametric partial differential equations—0
U-NO: U-shaped Neural OperatorsCode1
Error-in-variables modelling for operator learning—0
Deep transfer operator learning for partial differential equations under conditional shiftCode1
Multifidelity Deep Operator Networks For Data-Driven and Physics-Informed Problems—0
MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems—0
A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation MeasurementsCode0
Multi-Channel Convolutional Analysis Operator Learning for Dual-Energy CT ReconstructionCode0
On the influence of over-parameterization in manifold based surrogates and deep neural operatorsCode0
Convolutional Analysis Operator Learning by End-To-End Training of Iterative Neural NetworksCode0
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning—0
Learning Operators with Coupled AttentionCode1
Diffeomorphically Learning Stable Koopman OperatorsCode0
Adaptive Fourier Neural Operators: Efficient Token Mixers for TransformersCode1
Improved Model based Deep Learning using Monotone Operator Learning (MOL)—0
Solving PDE-constrained Control Problems Using Operator Learning—0
Physics-Informed Neural Operator for Learning Partial Differential EquationsCode1
Fast PDE-constrained optimization via self-supervised operator learningCode1
Improved architectures and training algorithms for deep operator networksCode1
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