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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 51–100 of 347 papers

TitleStatusHype
Diffeomorphism Neural Operator for various domains and parameters of partial differential equationsCode1
Improve Representation for Imbalanced Regression through Geometric ConstraintsCode1
Physics-Informed Neural Operator for Learning Partial Differential EquationsCode1
Deep transfer operator learning for partial differential equations under conditional shiftCode1
GNOT: A General Neural Operator Transformer for Operator LearningCode1
Multiwavelet-based Operator Learning for Differential EquationsCode1
A finite operator learning technique for mapping the elastic properties of microstructures to their mechanical deformationsCode1
Learning Efficient Abstract Planning Models that Choose What to PredictCode1
Generative AI for fast and accurate statistical computation of fluidsCode1
Fast Sampling of Diffusion Models via Operator LearningCode1
Guiding continuous operator learning through Physics-based boundary constraintsCode1
An operator learning perspective on parameter-to-observable mapsCode1
In-Context Operator Learning with Data Prompts for Differential Equation ProblemsCode1
NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform DataCode1
An enrichment approach for enhancing the expressivity of neural operators with applications to seismologyCode1
U-NO: U-shaped Neural OperatorsCode1
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context LearningCode1
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning—0
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning—0
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains—0
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis—0
A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics—0
Connecting the geometry and dynamics of many-body complex systems with message passing neural operators—0
Conformal Prediction on Quantifying Uncertainty of Dynamic Systems—0
An Enhanced V-cycle MgNet Model for Operator Learning in Numerical Partial Differential Equations—0
Fast and Accurate Reduced-Order Modeling of a MOOSE-based Additive Manufacturing Model with Operator Learning—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—0
Nonparametric Sparse Online Learning of the Koopman Operator—0
Composite Bayesian Optimization In Function Spaces Using NEON -- Neural Epistemic Operator Networks—0
Analysis Operator Learning and Its Application to Image Reconstruction—0
Component Fourier Neural Operator for Singularly Perturbed Differential Equations—0
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion—0
Analysis of Fast Structured Dictionary Learning—0
OmniFluids: Unified Physics Pre-trained Modeling of Fluid Dynamics—0
Analysis of Fast Alternating Minimization for Structured Dictionary Learning—0
Accelerated primal-dual methods with enlarged step sizes and operator learning for nonsmooth optimal control problems—0
A Mathematical Guide to Operator Learning—0
DPA-WNO: A gray box model for a class of stochastic mechanics problem—0
Domain Adaptive Safety Filters via Deep Operator Learning—0
Bridging scales in multiscale bubble growth dynamics with correlated fluctuations using neural operator learning—0
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators—0
Error-in-variables modelling for operator learning—0
Real-time Inference and Extrapolation via a Diffusion-inspired Temporal Transformer Operator (DiTTO)—0
Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification—0
Discretization Error of Fourier Neural Operators—0
Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction—0
Dynamic Gaussian Graph Operator: Learning parametric partial differential equations in arbitrary discrete mechanics problems—0
Derivative-informed neural operator acceleration of geometric MCMC for infinite-dimensional Bayesian inverse problems—0
DIMON: Learning Solution Operators of Partial Differential Equations on a Diffeomorphic Family of Domains—0
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