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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 276–300 of 347 papers

TitleStatusHype
Nonparametric Control Koopman Operators—0
On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators—0
One-shot learning for solution operators of partial differential equations—0
Online and Stable Learning of Analysis Operators—0
On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators—0
Operator Learning: Algorithms and Analysis—0
Operator Learning: A Statistical Perspective—0
Operator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions—0
Operator learning for hyperbolic partial differential equations—0
Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach—0
Operator Learning for Robust Stabilization of Linear Markov-Jumping Hyperbolic PDEs—0
Operator-learning-inspired Modeling of Neural Ordinary Differential Equations—0
Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods—0
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective—0
Operator learning regularization for macroscopic permeability prediction in dual-scale flow problem—0
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator LearningCode0
Ensemble and Mixture-of-Experts DeepONets For Operator LearningCode0
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular DynamicsCode0
Aero-Nef: Neural Fields for Rapid Aircraft Aerodynamics SimulationsCode0
Learning Where to Learn: Training Distribution Selection for Provable OOD PerformanceCode0
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific SimulationsCode0
LeMON: Learning to Learn Multi-Operator NetworksCode0
Leray-Schauder Mappings for Operator LearningCode0
Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström methodCode0
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator LearningCode0
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