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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 101–150 of 347 papers

TitleStatusHype
On the Benefits of Active Data Collection in Operator LearningCode0
On the limits of neural network explainability via descramblingCode0
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time GeneralizationCode0
Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical SystemsCode0
Neural Operator Learning for Ultrasound Tomography InversionCode0
Neural Operators for PDE Backstepping Control of First-Order Hyperbolic PIDE with Recycle and DelayCode0
DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC DesignCode0
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEsCode0
Multi-Resolution Active Learning of Fourier Neural OperatorsCode0
Importance Weight Estimation and Generalization in Domain Adaptation under Label ShiftCode0
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular DynamicsCode0
A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation MeasurementsCode0
Loss Terms and Operator Forms of Koopman AutoencodersCode0
Multi-Channel Convolutional Analysis Operator Learning for Dual-Energy CT ReconstructionCode0
Neural Functional: Learning Function to Scalar Maps for Neural PDE SurrogatesCode0
Learning Where to Learn: Training Distribution Selection for Provable OOD PerformanceCode0
LeMON: Learning to Learn Multi-Operator NetworksCode0
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator LearningCode0
Leray-Schauder Mappings for Operator LearningCode0
Interpreting and generalizing deep learning in physics-based problems with functional linear modelsCode0
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse ProblemsCode0
GIT-Net: Generalized Integral Transform for Operator LearningCode0
GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applicationsCode0
Geometry aware inference of steady state PDEs using Equivariant Neural Fields representationsCode0
Diffeomorphically Learning Stable Koopman OperatorsCode0
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström methodCode0
Nonlinear model reduction for operator learningCode0
Generic bounds on the approximation error for physics-informed (and) operator learning—0
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning—0
FUSE: Fast Unified Simulation and Estimation for PDEs—0
Functional SDE approximation inspired by a deep operator network architecture—0
Fredholm Integral Equations Neural Operator (FIE-NO) for Data-Driven Boundary Value Problems—0
Fourier-RNNs for Modelling Noisy Physics Data—0
Forecasting subcritical cylinder wakes with Fourier Neural Operators—0
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains—0
FLRONet: Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements—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
Neural Operator: Is data all you need to model the world? An insight into the impact of Physics Informed Machine Learning—0
Connecting the geometry and dynamics of many-body complex systems with message passing neural operators—0
Fast and Accurate Reduced-Order Modeling of a MOOSE-based Additive Manufacturing Model with Operator Learning—0
Error-in-variables modelling for operator learning—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
A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics—0
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning—0
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators—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
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