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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 1–25 of 347 papers

TitleStatusHype
A Library for Learning Neural OperatorsCode7
Neural Operators with Localized Integral and Differential KernelsCode4
Guaranteed Approximation Bounds for Mixed-Precision Neural OperatorsCode4
Poseidon: Efficient Foundation Models for PDEsCode3
Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary DomainsCode2
Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent FlowsCode2
CViT: Continuous Vision Transformer for Operator LearningCode2
Equivariant Graph Neural Operator for Modeling 3D DynamicsCode2
PDE Generalization of In-Context Operator Networks: A Study on 1D Scalar Nonlinear Conservation LawsCode2
Spherical Fourier Neural Operators: Learning Stable Dynamics on the SphereCode2
Convolutional Neural Operators for robust and accurate learning of PDEsCode2
Neural Operator: Learning Maps Between Function SpacesCode2
Mesh-Informed Neural Operator : A Transformer Generative ApproachCode1
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Improve Representation for Imbalanced Regression through Geometric ConstraintsCode1
RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domainsCode1
Point-DeepONet: A Deep Operator Network Integrating PointNet for Nonlinear Analysis of Non-Parametric 3D Geometries and Load ConditionsCode1
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problemsCode1
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics PredictionCode1
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic DevicesCode1
Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?Code1
Basis-to-Basis Operator Learning Using Function EncodersCode1
Generative AI for fast and accurate statistical computation of fluidsCode1
PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid DynamicsCode1
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