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Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

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Showing 126–150 of 347 papers

TitleStatusHype
Dilated convolution neural operator for multiscale partial differential equations—0
Bayesian Inversion with Neural Operator (BINO) for Modeling Subdiffusion: Forward and Inverse Problems—0
Adaptive operator learning for infinite-dimensional Bayesian inverse problems—0
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification—0
Diffeomorphic Latent Neural Operators for Data-Efficient Learning of Solutions to Partial Differential Equations—0
A Kernel Approach for PDE Discovery and Operator Learning—0
Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis—0
Artificial intelligence for partial differential equations in computational mechanics: A review—0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
DeepSeek vs. ChatGPT: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks—0
DeepOSets: Non-Autoregressive In-Context Learning of Supervised Learning Operators—0
A Resolution Independent Neural Operator—0
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs—0
Deep Operator Learning-based Surrogate Models with Uncertainty Quantification for Optimizing Internal Cooling Channel Rib Profiles—0
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning—0
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution—0
DeepONet for Solving Nonlinear Partial Differential Equations with Physics-Informed Training—0
DeepONet Augmented by Randomized Neural Networks for Efficient Operator Learning in PDEs—0
Approximation Rates in Fréchet Metrics: Barron Spaces, Paley-Wiener Spaces, and Fourier Multipliers—0
DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning—0
A Hybrid Kernel-Free Boundary Integral Method with Operator Learning for Solving Parametric Partial Differential Equations In Complex Domains—0
Accelerating Phase Field Simulations Through a Hybrid Adaptive Fourier Neural Operator with U-Net Backbone—0
Improved Model based Deep Learning using Monotone Operator Learning (MOL)—0
DeepOFormer: Deep Operator Learning with Domain-informed Features for Fatigue Life Prediction—0
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs—0
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