Highlights
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PINNs Public
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
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DeepHPMs Public
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
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Introduction to Machine Learning in R
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NumericalGP Public
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
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DeepVIV Public
Deep Learning of Vortex Induced Vibrations
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FBSNNs Public
Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
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MultistepNNs Public
Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
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DeepLearningTutorial Public
Tutorial on a number of topics in Deep Learning
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HPM Public
Hidden physics models: Machine learning of nonlinear partial differential equations
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ParametricGP Public
Parametric Gaussian Process Regression for Big Data
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DeepTurbulence Public
Deep Learning of Turbulent Scalar Mixing
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PDE_GP Public
Machine learning of linear differential equations using Gaussian processes
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ParametricGP-in-Matlab Public
Parametric Gaussian Process Regression for Big Data (Matlab Version)