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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 301–325 of 347 papers

TitleStatusHype
On the Benefits of Active Data Collection in Operator LearningCode0
Loss Terms and Operator Forms of Koopman AutoencodersCode0
On the limits of neural network explainability via descramblingCode0
On the influence of over-parameterization in manifold based surrogates and deep neural operatorsCode0
Diffeomorphically Learning Stable Koopman OperatorsCode0
ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian SensorsCode0
DPHGNN: A Dual Perspective Hypergraph Neural NetworksCode0
DFU: scale-robust diffusion model for zero-shot super-resolution image generationCode0
Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation ModelCode0
HyperbolicLR: Epoch insensitive learning rate schedulerCode0
DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC DesignCode0
Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential EquationsCode0
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator LearningCode0
Multi-Channel Convolutional Analysis Operator Learning for Dual-Energy CT ReconstructionCode0
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time GeneralizationCode0
Some Best Practices in Operator LearningCode0
Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equationsCode0
A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation MeasurementsCode0
Convolutional Analysis Operator Learning: Dependence on Training DataCode0
GIT-Net: Generalized Integral Transform for Operator LearningCode0
Multi-Resolution Active Learning of Fourier Neural OperatorsCode0
GFN: A graph feedforward network for resolution-invariant reduced operator learning in multifidelity applicationsCode0
Geometry aware inference of steady state PDEs using Equivariant Neural Fields representationsCode0
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse ProblemsCode0
Operator learning without the adjointCode0
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