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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 51–75 of 347 papers

TitleStatusHype
Equivariant Neural Operator Learning with Graphon ConvolutionCode1
Fine-Tune Language Models as Multi-Modal Differential Equation SolversCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Separable Operator NetworksCode1
Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and ExtrapolationCode1
Transformer for Partial Differential Equations' Operator LearningCode1
Continuum Attention for Neural OperatorsCode1
U-NO: U-shaped Neural OperatorsCode1
DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC DesignCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Guiding continuous operator learning through Physics-based boundary constraintsCode1
An operator learning perspective on parameter-to-observable mapsCode1
Learning Operators with Coupled AttentionCode1
Operator Learning with Neural Fields: Tackling PDEs on General GeometriesCode1
An enrichment approach for enhancing the expressivity of neural operators with applications to seismologyCode1
Fast PDE-constrained optimization via self-supervised operator learningCode1
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context LearningCode1
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning—0
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains—0
DeepSeek vs. ChatGPT: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks—0
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis—0
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis—0
A fast neural hybrid Newton solver adapted to implicit methods for nonlinear dynamics—0
Connecting the geometry and dynamics of many-body complex systems with message passing neural operators—0
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