
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
Circuits of biological neurons, such as in the functional parts of the b...
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Physics Informed Neural Networks for Simulating Radiative Transfer
We propose a novel machine learning algorithm for simulating radiative t...
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Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks
We present a novel active learning algorithm, termed as iterative surrog...
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Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs II: A class of inverse problems
Physics informed neural networks (PINNs) have recently been very success...
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Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs
Physics informed neural networks (PINNs) have recently been widely used ...
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Enhancing accuracy of deep learning algorithms by training with lowdiscrepancy sequences
We propose a deep supervised learning algorithm based on lowdiscrepancy...
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On the approximation of rough functions with deep neural networks
Deep neural networks and the ENO procedure are both efficient frameworks...
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A Multilevel procedure for enhancing accuracy of machine learning algorithms
We propose a multilevel method to increase the accuracy of machine lear...
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Statistical solutions of the incompressible Euler equations
We propose and study the framework of dissipative statistical solutions ...
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Deep learning observables in computational fluid dynamics
Many large scale problems in computational fluid dynamics such as uncert...
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Siddhartha Mishra
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