Maziar Raissi

PINNs. Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

Applied-Deep-Learning. Applied Deep Learning Course

HFM. Hidden Fluid Mechanics

DeepHPMs. Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

FBSNNs. Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

HPM. Hidden physics models: Machine learning of nonlinear partial differential equations

PetGPT. Train your own PetGPT at home!

DeepVIV. Deep Learning of Vortex Induced Vibrations

NumericalGP. Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations

MultistepNNs. Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems

TutorialGP. Tutorial on Gaussian Processes

backprop. Backpropagation in Python, C++, and Cuda

ParametricGP. Parametric Gaussian Process Regression for Big Data

DeepLearningTutorial. Tutorial on a number of topics in Deep Learning

PDE_GP. Machine learning of linear differential equations using Gaussian processes

Introduction-to-Machine-Learning-in-R. Introduction to Machine Learning in R

ParametricGP-in-Matlab. Parametric Gaussian Process Regression for Big Data (Matlab Version)

DeepTurbulence. Deep Learning of Turbulent Scalar Mixing

APPM_Colloquium. Applied Mathematics (APPM) Department Colloquium