finmod
finmod
There is no docs on the command `full_equations()`, its relation to `structural_simplify`, ODAE systems and differences with `equations()`.
@iliailmer and @ChrisRackauckas Great addition to MTK tutorials on DAE-ODE systems. Just like to mention typos at "We will start by **illustrating** local identifiability" and "In this part **of the**...
See this https://royalsocietypublishing.org/doi/full/10.1098/rsif.2017.0871 A new class of functions, called the ‘information sensitivity functions’ (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are...
Another approach to address the ill-conditioning of the medium-sized parameter sensitivity matrix is the likelihood profiler method proposed here: https://github.com/insysbio/LikelihoodProfiler.jl/issues/3#issuecomment-548871929
The state-of-the-art inspiration to estimate_delay is nicely condensed in the thesis of Jan Schumann-Bischoff which you can find here: https://d-nb.info/1116709740/34. Chapter 9 on the Shinriki oscillator has all the ingredients...
@ChrisRackauckas This MFGnet.jl package is significant in applying Lagrangian methods to MFG and therefore lessening the curse of dimensionality in this class of problems (dimension from 2 to 100 in...
Running the Lorenz param estim example, the estimated parameters are: 3-element Vector{Float64}: 10.000484105285961 27.99897160477475 2.667291549846074 Then in the graphical analysis: initθ = discretization.init_params acum = [0;accumulate(+, length.(initθ))] sep = [acum[i]+1...
https://arxiv.org/pdf/1909.12678.pdf . The problem set of NeuralNetDiffEq should be extended to this MKV FBSPDE problem with numerical comparison with Python results.
Introduce in the "features" section of docs, a roadmap of development of NeuralPDE along the line of section 3 of https://arxiv.org/abs/2101.08068 that is in two parts: A deterministic approach by...