SOTAVerified

Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

Showing 101–150 of 347 papers

TitleStatusHype
State-space models are accurate and efficient neural operators for dynamical systemsCode0
Spatio-spectral graph neural operator for solving computational mechanics problems on irregular domain and unstructured grid—0
LeMON: Learning to Learn Multi-Operator NetworksCode0
An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning—0
Fredholm Integral Equations Neural Operator (FIE-NO) for Data-Driven Boundary Value Problems—0
Total Uncertainty Quantification in Inverse PDE Solutions Obtained with Reduced-Order Deep Learning Surrogate Models—0
Transfer Operator Learning with Fusion Frame—0
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators—0
Operator Learning Using Random Features: A Tool for Scientific ComputingCode1
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem SolvingCode0
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification—0
Aero-Nef: Neural Fields for Rapid Aircraft Aerodynamics SimulationsCode0
Solving the Electrical Impedance Tomography Problem with a DeepONet Type Neural Network: Theory and Application—0
HyperbolicLR: Epoch insensitive learning rate schedulerCode0
A Resolution Independent Neural Operator—0
Dilated convolution neural operator for multiscale partial differential equations—0
Separable Operator NetworksCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics—0
Green Multigrid Network—0
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning—0
Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective—0
Accelerating Phase Field Simulations Through a Hybrid Adaptive Fourier Neural Operator with U-Net Backbone—0
Optimal deep learning of holomorphic operators between Banach spaces—0
Projection Methods for Operator Learning and Universal Approximation—0
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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