pyABC
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ICB-DCM
distributed, likelihood-free inference
* Add JOSS paper of version 0.12.5 * Update Julia reference DiffEqJump -> JumpProcesses (name change)
a Dash webserver to visualize pyABC output directly from the database file.
I'm following the example: https://pyabc.readthedocs.io/en/latest/examples/using_julia.html?highlight=julia I've put the code in the example in a python file test.py shown below. SIR.jl is exactly the same as in the example. Running test.py...
Dear @yannikschaelte, The script reported an error when I ran the pyABC script. Do you have any idea about this error? Is this caused by the SQL storage? Thank you!...
Implement a set of common ABC test and application problems with common API (prior, ground truth, data, model, ...) - [ ] simple Gaussian of dim n with estimated mean...
**Feature description** From the corresponding paper Simola et al. 2021 https://projecteuclid.org/journals/bayesian-analysis/volume-16/issue-2/Adaptive-Approximate-Bayesian-Computation-Tolerance-Selection/10.1214/20-BA1211.full **Motivation/Application** Adaptive quantile selection, with promising results reported in the paper. **Difficulty** Not too difficult, just may require some...
Provide an accessible overview page of highlight algorithms implemented in pyABC (as well as corresponding publications for further details).
**Feature description** It would be great to have a sampler that's both compatible with JAX-jitted functions and leverages JAX's parallelization tools. **Motivation/Application** I have a slow objective function that is...
It is cleaner to manually define a random state, pass it to pyabc and then also to all workers (appropriately reinitialized). This would allow increasing the degree of reproducibility (there...