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**Description of problem:**
When using the age-structured model, the number of social interactions within the population is controlled using the 'total' interaction matrix $N_c$. This is a 16x16 ma…
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There are a number of contexts were discrete variables are required to perform optimization, specifically multi-task optimization at discrete fidelities.
TODO list:
- implement discrete variable s…
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Hey there,
I found your project which seems promising for a problem, I am currently working on.
However, I as far as I can see, the option to include discrete variables in the optimization is not ye…
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When there is a lot of steps recorded, tensorboard uses discretization for optimization. It is unexpected loss of information, but it's fine. However, when using EMA smoothing, differently discretized…
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Hello Marco !
I now have a new optimization problem, which is very demanding computationally (several biological systems in different MD simulations at each evaluation during optimization) and most…
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Have there been any thoughts of implementing an optimization routine (with interface to Python) that can optimize multiple types of parameters at once? This is often needed when optimizing machine lea…
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This issue is for more of an API discussion before I dig in to implement PINO PDE. Here I provide examples of supposed API for Physics Informed Neural operator (PINO) problem.
articles
https://…
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read:
### stochastic programming
mathematical programming book
http://web.mit.edu/15.053/www/AMP.htm
mutistage stochastic programming
https://orbi.uliege.be/bitstream/2268/80246/1/MSPchap_pre…
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Hello!
It seems like currently the discrete models could be fitted only with HN elements.
Is there any way to apply other basic elements like RC, RQ or ZARC?
BR
Artem Pushkarev
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see #3845, and companion to #4229
The following are the convergence warnings with discrete models, in base and discrete unit tests.
from https://travis-ci.org/statsmodels/statsmodels/jobs/3334451…