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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
Improve Representation for Imbalanced Regression through Geometric ConstraintsCode1
Basis-to-Basis Operator Learning Using Function EncodersCode1
Deep transfer operator learning for partial differential equations under conditional shiftCode1
Operator Learning with Neural Fields: Tackling PDEs on General GeometriesCode1
GNOT: A General Neural Operator Transformer for Operator LearningCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Continuum Attention for Neural OperatorsCode1
Mesh-Informed Neural Operator : A Transformer Generative ApproachCode1
A finite operator learning technique for mapping the elastic properties of microstructures to their mechanical deformationsCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Generative AI for fast and accurate statistical computation of fluidsCode1
An operator learning perspective on parameter-to-observable mapsCode1
Guiding continuous operator learning through Physics-based boundary constraintsCode1
In-Context Operator Learning with Data Prompts for Differential Equation ProblemsCode1
An enrichment approach for enhancing the expressivity of neural operators with applications to seismologyCode1
NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform DataCode1
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context LearningCode1
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
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning—0
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition—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
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
Accelerated primal-dual methods with enlarged step sizes and operator learning for nonsmooth optimal control problems—0
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators—0
A Mathematical Guide to Operator Learning—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
Error-in-variables modelling for operator learning—0
Fast and Accurate Reduced-Order Modeling of a MOOSE-based Additive Manufacturing Model with Operator Learning—0
FLRONet: Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements—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
DPA-WNO: A gray box model for a class of stochastic mechanics problem—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
Analysis of Fast Alternating Minimization for Structured Dictionary Learning—0
DIMON: Learning Solution Operators of Partial Differential Equations on a Diffeomorphic Family of Domains—0
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