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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
Physics-Informed Latent Neural Operator for Real-time Predictions of Complex Physical Systems—0
Orthogonal greedy algorithm for linear operator learning with shallow neural network—0
Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach—0
Approximation Rates in Fréchet Metrics: Barron Spaces, Paley-Wiener Spaces, and Fourier Multipliers—0
Point-DeepONet: A Deep Operator Network Integrating PointNet for Nonlinear Analysis of Non-Parametric 3D Geometries and Load ConditionsCode1
KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics—0
A Library for Learning Neural OperatorsCode7
Conformal Prediction on Quantifying Uncertainty of Dynamic Systems—0
Operator Learning for Robust Stabilization of Linear Markov-Jumping Hyperbolic PDEs—0
A physics-informed transformer neural operator for learning generalized solutions of initial boundary value problemsCode1
FLRONet: Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements—0
Adversarial Autoencoders in Operator LearningCode0
Some Best Practices in Operator LearningCode0
Nonlinear Operator Learning Using Energy Minimization and MLPs—0
Loss Terms and Operator Forms of Koopman AutoencodersCode0
Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems—0
Operator learning regularization for macroscopic permeability prediction in dual-scale flow problem—0
Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems—0
Diffeomorphic Latent Neural Operators for Data-Efficient Learning of Solutions to Partial Differential Equations—0
U-WNO:U-Net-enhanced Wavelet Neural Operator for fetal head segmentation—0
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics PredictionCode1
DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning—0
Mitigating Stop-and-Go Traffic Congestion with Operator Learning—0
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic DevicesCode1
The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures—0
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