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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
DCEM: A deep complementary energy method for solid mechanicsCode1
Sharp Spectral Rates for Koopman Operator LearningCode1
Guiding continuous operator learning through Physics-based boundary constraintsCode1
Transform Once: Efficient Operator Learning in Frequency DomainCode1
Fast Sampling of Diffusion Models via Operator LearningCode1
Learning dynamical systems: an example from open quantum system dynamicsCode1
Learning Efficient Abstract Planning Models that Choose What to PredictCode1
Transformer for Partial Differential Equations' Operator LearningCode1
U-NO: U-shaped Neural OperatorsCode1
Deep transfer operator learning for partial differential equations under conditional shiftCode1
Learning Operators with Coupled AttentionCode1
Adaptive Fourier Neural Operators: Efficient Token Mixers for TransformersCode1
Physics-Informed Neural Operator for Learning Partial Differential EquationsCode1
Fast PDE-constrained optimization via self-supervised operator learningCode1
Improved architectures and training algorithms for deep operator networksCode1
Multiwavelet-based Operator Learning for Differential EquationsCode1
Choose a Transformer: Fourier or GalerkinCode1
Learning Symbolic Operators for Task and Motion PlanningCode1
OmniFluids: Unified Physics Pre-trained Modeling of Fluid Dynamics—0
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
Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical SystemsCode0
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