ModelingToolkit.jl Alternatives

ModelingToolkit.jl reviews and mentions

• Modelica
  11 projects | news.ycombinator.com | 16 Dec 2024

  JuliaSim looks interesting! From my understanding, it's 100% proprietary/commercial, but built on top of the open source https://github.com/SciML/ModelingToolkit.jl?

• Mathematically Modelling a PRV
  1 project | /r/ControlTheory | 24 Oct 2022

  I'd use a modeling tool like https://mtk.sciml.ai/dev/ Using the standard library, you wouldn't need to come up with all equations yourself. Depending on the details of your use case, system identification as suggested before might be a faster approach though.

• Simulating a simple circuit with the ModelingToolkit
  2 projects | /r/Julia | 29 Jun 2022
• “Why I still recommend Julia”
  11 projects | news.ycombinator.com | 25 Jun 2022
• ‘Machine Scientists’ Distill the Laws of Physics from Raw Data
  8 projects | news.ycombinator.com | 10 May 2022
• How do I force it to answer in a decimal format.
  1 project | /r/matlab | 13 Mar 2022

  In this case, yes, this should just be done numerically. But using symbolic transformations to optimize numeric code is also a really neat application of symbolic computing that doesn't get enough attention, imo. [This library](https://github.com/SciML/ModelingToolkit.jl), for example, uses symbolics to do sparsity detection, automatic derivative/gradient/jacobian/hessian calculations, index reduction, etc. to speed up numerical differential equation solving.

• Julia 1.7 has been released
  15 projects | news.ycombinator.com | 30 Nov 2021
• [Research] Input Arbitrary PDE -> Output Approximate Solution
  4 projects | /r/MachineLearning | 10 Jul 2021

  PDEs are difficult because you don't have a simple numerical definition over all PDEs because they can be defined by arbitrarily many functions. u' = Laplace u + f? Define f. u' = g(u) * Laplace u + f? Define f and g. Etc. To cover the space of PDEs you have to go symbolic at some point, and make the discretization methods dependent on the symbolic form. This is precisely what the ModelingToolkit.jl ecosystem is doing. One instantiation of a discretizer on this symbolic form is NeuralPDE.jl which takes a symbolic PDESystem and generates an OptimizationProblem for a neural network which represents the solution via a Physics-Informed Neural Network (PINN).

• Should I switch over completely to Julia from Python for numerical analysis/computing?
  5 projects | /r/Julia | 8 Jul 2021

  There's a very clear momentum for Julia here in this domain of modeling and simulation. With JuliaSim funding an entire modeling and simulation department within Julia Computing dedicated to building out an ecosystem that accelerates this domain and the centralization around the SciML tooling, this is an area where we absolutely have both a manpower and momentum advantage. We're getting many universities (PhD students and professors) involved on the open source side, while building out different commercial tools and GUIs on top of the open numerical core. The modeling and simulation domain itself is soon going to have its own SciMLCon since our developer community has gotten too large to just be a few JuliaCon talks: it needs its own days to fit everyone! Not only that, in many aspects we're not just moving faster but have already passed. Not in every way, there's still some important discussion in controls that needs to happen, but that's what the momentum is for.

• What should a graduate engineer know about MATLAB?
  2 projects | /r/engineering | 26 Apr 2021
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