6 results found Sort:
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
pinn
stiff-ode
neural-dde
neural-ode
neural-pde
neural-sde
neural-sdes
scientific-ai
scientific-ml
neural-networks
differentialequations
differential-equations
neural-jump-diffusions
physics-informed-learning
scientific-machine-learning
delay-differential-equations
neural-differential-equations
partial-differential-equations
ordinary-differential-equations
stochastic-differential-equations
Created
2018-12-26
1,927 commits to master branch, last one 6 days ago
Automatic Finite Difference PDE solving with Julia SciML
Created
2021-12-13
1,208 commits to master branch, last one about a month 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