Kaan Öcal

Results 24 issues of Kaan Öcal

Taken from [this issue](https://github.com/theogf/AugmentedGaussianProcesses.jl/issues/88#issuecomment-849919054_) in AugmentedGaussianProcesses.jl: > There seems to be no simple way of accessing observations in a PosteriorGP except via data.x and data.δ As there is a standard...

Some applications require HMMs where the transition matrices and/or the output distributions vary with time. Since these are simple modifications I created an experimental fork with support for these -...

I've implemented a simple version of the standard AM algorithm as a small extension to #39 (this PR is independent of #39). The pull request features a multivariate Gaussian proposal...

```julia prob = ODEProblem((du, u, p, t) -> du .= 0, ArrayPartition([0.]), (0, 10.)) jump = VariableRateJump((u, p, t) -> 1, int -> (int.u += 1)) jprob = JumpProblem(prob, Direct(),...

I'm not sure if this has been noted before, but creating a very simple chain or attempting to slice a chain in interactive mode (REPL, notebook) etc. fails: ```julia using...

I am currently using [Stan](https://mc-stan.org/) and want to read the rather large CSV output files it generates in Julia. These can contain thousands of lines and columns, the typical file...

performance

It is sometimes useful to perform MH in a reparametrised space, similar to HMC with its bijectors. This would effectively allow for non-stationary Gaussian proposals, among others. It does not...

The following causes a StackOverflowError: ```julia using DynamicPolynomials promote_type(Any, Polynomial{true,Any}) ``` Here `Any` can be replaced by various types. Output: ```julia ERROR: StackOverflowError: Stacktrace: [1] promote_result(#unused#::Type, #unused#::Type, #unused#::Type{Any}, #unused#::Type{DynamicPolynomials.Polynomial{true, Any}})...

Parameters in `ModelingToolkit` can be passed as `(name, value)` pairs or dictionaries. Example: ```julia rn = @reaction_network begin s, 0 -> A d, A -> 0 end dprob = DiscreteProblem(rn,...

The following is a valid Julia function: ```(a, (b, d), e) -> d + e``` but doesn't work with RuntimeGeneratedFunctions (`normalize_args` throws an error). I've tried adding an override for...