SOTAVerified

Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 347 papers

TitleStatusHype
Deep Learning Computed Tomography based on the Defrise and Clack AlgorithmCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Generative AI for fast and accurate statistical computation of fluidsCode1
In-Context Operator Learning with Data Prompts for Differential Equation ProblemsCode1
An operator learning perspective on parameter-to-observable mapsCode1
Learning Efficient Abstract Planning Models that Choose What to PredictCode1
Improved architectures and training algorithms for deep operator networksCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context LearningCode1
Guiding continuous operator learning through Physics-based boundary constraintsCode1
Improved Operator Learning by Orthogonal AttentionCode1
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problemsCode1
Continuum Attention for Neural OperatorsCode1
Adaptive Fourier Neural Operators: Efficient Token Mixers for TransformersCode1
Deciphering and integrating invariants for neural operator learning with various physical mechanismsCode1
DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC DesignCode1
Basis-to-Basis Operator Learning Using Function EncodersCode1
Diffeomorphism Neural Operator for various domains and parameters of partial differential equationsCode1
Kernel Methods are Competitive for Operator LearningCode1
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator LearningCode1
DCEM: A deep complementary energy method for solid mechanicsCode1
Equivariant Neural Operator Learning with Graphon ConvolutionCode1
Fast Sampling of Diffusion Models via Operator LearningCode1
An enrichment approach for enhancing the expressivity of neural operators with applications to seismologyCode1
A finite operator learning technique for mapping the elastic properties of microstructures to their mechanical deformationsCode1
Show:102550
← PrevPage 2 of 14Next →

No leaderboard results yet.