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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 1–10 of 347 papers

TitleStatusHype
Mesh-Informed Neural Operator : A Transformer Generative ApproachCode1
OmniFluids: Unified Physics Pre-trained Modeling of Fluid Dynamics—0
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
Mondrian: Transformer Operators via Domain Decomposition—0
PMNO: A novel physics guided multi-step neural operator predictor for partial differential equations—0
Learning Where to Learn: Training Distribution Selection for Provable OOD PerformanceCode0
Recurrent Neural Operators: Stable Long-Term PDE Prediction—0
Graph-Based Operator Learning from Limited Data on Irregular Domains—0
Geometry Aware Operator Transformer as an Efficient and Accurate Neural Surrogate for PDEs on Arbitrary DomainsCode2
Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical SystemsCode0
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