ThummeTo's repositories
FMIFlux.jl
FMIFlux.jl is a free-to-use software library for the Julia programming language, which offers the ability to place FMUs (fmi-standard.org) everywhere inside of your ML topologies and still keep the resulting model trainable with a standard (or custom) FluxML training process.
DifferentiableEigen.jl
The current implementation of `LinearAlgebra.eigen` does not support sensitivities. DifferentiableEigen.jl offers an `eigen` function that is differentiable by every AD-framework with support for ChainRulesCore.jl or ForwardDiff.jl.
FMIExport.jl
FMIExport.jl is a free-to-use software library for the Julia programming language which allows for the export of FMUs (fmi-standard.org) from any Julia-Code. FMIExport.jl is completely integrated into FMI.jl.
FMIImport.jl
FMIImport.jl implements the import functionalities of the FMI-standard (fmi-standard.org) for the Julia programming language. FMIImport.jl provides the foundation for the Julia packages FMI.jl and FMIFlux.jl.
FMICore.jl
FMICore.jl implements the low-level equivalents of the C-functions and C-data types of the FMI-standard (fmi-standard.org) for the Julia programming language.
FMIBuild.jl
FMIBuild.jl holds dependencies that are required to compile and zip a Functional Mock-Up Unit (FMU) compliant to the FMI-standard (fmi-standard.org). Because this dependencies should not be part of the compiled FMU, they are out-sourced into this package. FMIBuild.jl provides the build-commands for the Julia package FMIExport.jl.
DistributedHyperOpt.jl
DistributedHyperOpt.jl is a package similar to HyperOpt.jl, but explicitly focusing on distributed (multi-processing) hyperparameter optimization by design.
FMISensitivity.jl
Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event
FMIBase.jl
FMIBase.jl provides the foundation for the Julia packages FMIImport.jl and FMIExport.jl.
DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
EasyFit.jl
Easy interface for obtaining fits for 2D data
fmi-cross-check
Results and FMUs for the FMI Cross-Check
DiffEqCallbacks.jl
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
fmi-standard.org
Website of the Functional Mock-Up Interface (FMI)
NumericalIntegration.jl
Basic numerical integration routines for presampled data.
ReverseDiff.jl
Reverse Mode Automatic Differentiation for Julia
SciMLBase.jl
The Base interface of the SciML ecosystem
SciMLSensitivity.jl
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.