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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 126–150 of 347 papers

TitleStatusHype
Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications—0
Hamilton-Jacobi Based Policy-Iteration via Deep Operator Learning—0
Continuum Attention for Neural OperatorsCode1
M2NO: Multiresolution Operator Learning with Multiwavelet-based Algebraic Multigrid Method—0
GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applicationsCode0
Learning the Hodgkin-Huxley Model with Operator Learning Techniques—0
Solving Partial Differential Equations in Different Domains by Operator Learning method Based on Boundary Integral Equations—0
Physics and geometry informed neural operator network with application to acoustic scattering—0
Poseidon: Efficient Foundation Models for PDEsCode3
Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity—0
Infinite-dimensional Diffusion Bridge Simulation via Operator LearningCode0
Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent FlowsCode2
Deep Koopman Learning using Noisy Data—0
DPHGNN: A Dual Perspective Hypergraph Neural NetworksCode0
Data Complexity Estimates for Operator Learning—0
FUSE: Fast Unified Simulation and Estimation for PDEs—0
CViT: Continuous Vision Transformer for Operator LearningCode2
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains—0
Ensemble and Mixture-of-Experts DeepONets For Operator LearningCode0
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution—0
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator LearningCode1
Nonparametric Sparse Online Learning of the Koopman Operator—0
Nonparametric Control Koopman Operators—0
Learning Flame Evolution Operator under Hybrid Darrieus Landau and Diffusive Thermal Instability—0
Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric spaceCode0
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