Christopher Rackauckas

icon indicating a website link www.chrisrackauckas.com icon indicating an email [email protected]

icon company Massachusetts Institute of Technology icon location Cambridge, MA icon location Applied Mathematics Instructor at MIT, researching numerical differential equations and their applications to scientific machine learning (SciML)

Results 3987 comments of Christopher Rackauckas
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Summary of breakages when updating problems with conservation laws

SteadyStateProblems would use it because those use the ODEProblem. If they end up as a NonlinearProblem though it would be ignored since it should be inconsequential to the solution? For...

Summary of breakages when updating problems with conservation laws

> For NonlinearProblems one can specify an initial guess via value mappings of unknowns right? Yes, and that could be useful since starting with the conservation supported should keep it...

CaoTauLeaping Implementation

There are 3 schemes in the paper https://people.cs.vt.edu/~ycao/publication/newstepsize.pdf, can you implement them as different algorithms (reusing most of the code, just different controller dispatches) so we can compare them?

update unicode "₊" separator to use the default separator variable

https://github.com/SciML/Catalyst.jl/pull/951

update unicode "₊" separator to use the default separator variable

Just use the general separator const?

Large change in solver behavior after recent update (e.g., steady state not approached by solver)

I really don't have much to go on here 😅 . Is this using SteadyStateProblem? What solver? Automatic differentiation?

Large change in solver behavior after recent update (e.g., steady state not approached by solver)

You're near the edge of floating point precision there, so it's going to be hard for it to do much more than that and it would be a bit random...

MTK system type instability with physics-informed neural networks for parameter estimation for ODEs

The parameters don't seem right here. MTK generates equations with an MTKParameters object. `θ` would be the concatenation of the ODE parameters and the NN parameters, which I think it's...

MTK system type instability with physics-informed neural networks for parameter estimation for ODEs

> With PINNs the vector field du can deviate from the model allowing us to also capture some deviations from the model which are likely present in the experiment. And...

test: test coverage needs improvement for the ./src/utils.jl file

I don't think that's quite it. The issue is that the tests are split into many groups https://github.com/SciML/Optimization.jl/blob/master/.github/workflows/CI.yml#L22-L38 and I don't think the codecov system is merging them all right....