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08/10/2023
Filtering Dynamical Systems Using Observations of Statistics
We consider the problem of filtering dynamical systems, possibly stochas...
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02/09/2023
Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures
Bayesian posterior distributions arising in modern applications, includi...
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08/19/2021
Neural Operator: Learning Maps Between Function Spaces
The classical development of neural networks has primarily focused on le...
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06/13/2021
Markov Neural Operators for Learning Chaotic Systems
Chaotic systems are notoriously challenging to predict because of their ...
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10/18/2020
Fourier Neural Operator for Parametric Partial Differential Equations
The classical development of neural networks has primarily focused on le...
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06/16/2020
Multipole Graph Neural Operator for Parametric Partial Differential Equations
One of the main challenges in using deep learning-based methods for simu...
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05/13/2020
Kernel Analog Forecasting: Multiscale Test Problems
Data-driven prediction is becoming increasingly widespread as the volume...
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03/07/2020
Neural Operator: Graph Kernel Network for Partial Differential Equations
The classical development of neural networks has been primarily for mapp...
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08/31/2017