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Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
Created 2017-03-14
2,727 commits to master branch, last one 6 days ago
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Created 2018-12-26
1,927 commits to master branch, last one 6 days ago
Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
Created 2017-02-04
1,556 commits to master branch, last one about a month ago
Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
Created 2017-07-24
800 commits to master branch, last one about a month ago
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Created 2016-10-20
308 commits to master branch, last one 25 days ago
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
Created 2016-10-28
751 commits to master branch, last one about a month ago