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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 301–347 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
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators—0
Multiwavelet-based Operator Learning for Differential EquationsCode1
Neural Operator: Learning Maps Between Function SpacesCode2
Known Operator Learning and Hybrid Machine Learning in Medical Imaging --- A Review of the Past, the Present, and the Future—0
Choose a Transformer: Fourier or GalerkinCode1
One-shot learning for solution operators of partial differential equations—0
Learning Symbolic Operators for Task and Motion PlanningCode1
Learning the Update Operator for 2D/3D Image Registration—0
Importance Weight Estimation and Generalization in Domain Adaptation under Label ShiftCode0
On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators—0
Towards Scalable Koopman Operator Learning: Convergence Rates and A Distributed Learning Algorithm—0
Convolutional Analysis Operator Learning: Dependence on Training DataCode0
Analysis of Fast Structured Dictionary Learning—0
Convolutional Analysis Operator Learning: Acceleration and ConvergenceCode0
Analysis of Fast Alternating Minimization for Structured Dictionary Learning—0
Image operator learning coupled with CNN classification and its application to staff line removal—0
Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification—0
Image Fusion With Cosparse Analysis Operator—0
Online and Stable Learning of Analysis Operators—0
Separable Cosparse Analysis Operator Learning—0
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs—0
Analysis Operator Learning and Its Application to Image Reconstruction—0
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