Pinned Repositories
DataDrivenDiffEq.jl
Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
DeepEquilibriumNetworks.jl
Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
DelayDiffEq.jl
Delay differential equation solvers for the SciML scientific machine learning ecosystem
EasyModelAnalysis.jl
High level functions for analyzing the output of simulations
Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
Julia-test
testmepls
mfncheck
Implementation of papers in 100 lines of code.
MLFlowClient.jl
Julia client for MLFlow.
ModelingToolkit.jl
A modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Stiff-net.jl
In progress implementation of using stiff solvers as a means for NNs to update it's weights and learn stiff dynamics
AnasAbdelR's Repositories
AnasAbdelR/Stiff-net.jl
In progress implementation of using stiff solvers as a means for NNs to update it's weights and learn stiff dynamics
AnasAbdelR/DataDrivenDiffEq.jl
Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
AnasAbdelR/DeepEquilibriumNetworks.jl
Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
AnasAbdelR/DelayDiffEq.jl
Delay differential equation solvers for the SciML scientific machine learning ecosystem
AnasAbdelR/EasyModelAnalysis.jl
High level functions for analyzing the output of simulations
AnasAbdelR/Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
AnasAbdelR/Julia-test
testmepls
AnasAbdelR/mfncheck
Implementation of papers in 100 lines of code.
AnasAbdelR/MLFlowClient.jl
Julia client for MLFlow.
AnasAbdelR/ModelingToolkit.jl
A modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
AnasAbdelR/NeuralOperators.jl
learning the solution operator for partial differential equations in pure Julia.
AnasAbdelR/ODEInterfaceDiffEq.jl
Adds the common API onto ODEInterface classic Fortran methods for the SciML Scientific Machine Learning organization
AnasAbdelR/OrdinaryDiffEq.jl
High performance differential equation solvers for ordinary differential equations, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
AnasAbdelR/QuasiMonteCarlo.jl
Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)
AnasAbdelR/ReservoirComputing.jl
Reservoir computing utilities for scientific machine learning (SciML)
AnasAbdelR/sciml.ai
The SciML Scientific Machine Learning Software Organization Website
AnasAbdelR/StochasticDiffEq.jl
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
AnasAbdelR/Sundials.jl
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner
AnasAbdelR/TA3_Evaluation_Resources
Some materials for the TA3 2nd Hackathon