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Hello,
I'm solving some stiff DAEs with a mass-matrix solver in the following code:
```julia
using DifferentialEquations
include("model.jl")
pars = [7.33234842e-08,6.40146313e-12,1.56954148e-13…
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Right now, the `//systems/framework` notionally supports user-defined scalar types, because we (try to) place all of the code in header files templated on `T`. However, in practice possibly we have m…
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Hi all !
I was wondering, why did you choose to use chunk-wise forward AD, and not use http://www.juliadiff.org ?
Best,
Emile
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I did some parameter estimation, similar to the test problem in DiffEqParamEstim (https://github.com/JuliaDiffEq/DiffEqParamEstim.jl/blob/master/test/dde_tests.jl):
```julia
julia> using DelayDiffEq…
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I am interested in autodifferentiating the map that takes an initial value to its "final" value of an ODE solution. Taking the Lorenz example from the docs, I tried the following:
```
using Differ…
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I'm trying to learn from my mistakes, so this time I'll open an issue here instead of [posting at Discourse](https://discourse.julialang.org/t/need-help-interpreting-an-error-message-differentialequat…
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The idea for this package is to setup differentiation functions which utilize as much of the performance overloads as possible, and make it easily available for all of the native Julia solvers. The i…
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Instead of using trait dispatch which is inherently unsound after 265, we should instead create a function-holder type like Optim does. This type would just hold a bunch of functions, and then have th…
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DiffEqDiffTools supports much faster finite differencing routines than Calculus.
Ref: discussion on gitter.
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I am sorry to bother you with this. I am investigating the usage of autodifferentiation to provide efficent gradient descent updates for neural network training in Clojure. Unfortunately all the Schem…
whilo updated
7 years ago