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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 26–50 of 347 papers

TitleStatusHype
Inverted Gaussian Process Optimization for Nonparametric Koopman Operator Discovery—0
New universal operator approximation theorem for encoder-decoder architectures (Preprint)—0
DeepOFormer: Deep Operator Learning with Domain-informed Features for Fatigue Life Prediction—0
EquiNO: A Physics-Informed Neural Operator for Multiscale SimulationsCode0
Invertible Koopman neural operator for data-driven modeling of partial differential equations—0
Data-Driven, ML-assisted Approaches to Problem Well-Posedness—0
Theory-to-Practice Gap for Neural Networks and Neural Operators—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian SensorsCode0
Active operator learning with predictive uncertainty quantification for partial differential equations—0
Improve Representation for Imbalanced Regression through Geometric ConstraintsCode1
Cauchy Random Features for Operator Learning in Sobolev SpaceCode0
DeepONet Augmented by Randomized Neural Networks for Efficient Operator Learning in PDEs—0
Learning Hamiltonian Density Using DeepONet—0
High-fidelity Multiphysics Modelling for Rapid Predictions Using Physics-informed Parallel Neural Operator—0
DeepSeek vs. ChatGPT: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks—0
Connecting the geometry and dynamics of many-body complex systems with message passing neural operators—0
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion—0
Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data—0
Optimization for Neural Operators can Benefit from Width—0
RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domainsCode1
Multi-Physics Simulations via Coupled Fourier Neural Operator—0
In-Context Operator Learning for Linear Propagator Models—0
MeshONet: A Generalizable and Efficient Operator Learning Method for Structured Mesh Generation—0
ELM-DeepONets: Backpropagation-Free Training of Deep Operator Networks via Extreme Learning Machines—0
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