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A starting point for consideration is at https://github.com/rgrumbine/ice_scoring
This is organized largely by parameter to be examined -- concentration field, ice edge, ice drift being the most …
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Dear beloved OpenMole community,
as part of the general principles of reproducible research, for which OpenMole is so much valuable, the generation of graphs and other descriptive statistics would …
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As the abstract strategy templates are almost finished (https://github.com/experimental-design/bofire/pull/12), we should to discuss the how and who regarding bringing back of the strategies:
- Ran…
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# Overview
#228 prototyped a great initial integration with optuna to do hyperparameter optimization. However, it has a couple of downsides:
1. lack of support for tuning multiple environments …
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Hi,
Thanks for making this package!
I am trying to understand the performance of my `rmoo` results. I know that vignettes are forthcoming on using `getFitness()`, `getMetrics()` and `summary()`.…
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When performing optimization, we collect different measurements. A careful review over the involved metrics and the necessary information should be considered.
This should be documented properly. …
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Website needs some useful insights and stats from UQ submissions.
Although having UQ in the raw data is clearly useful, It is not useful to have UQ info on the website if no insight can be gleaned …
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I have a multi-objective optimization problem where my batched fitness function returns a result in the shape of `(30, 2)` (so 2 objectives). The settings for the optimizer are as follows:
```pyth…
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This could be an enhancement to OGIA, or a new algorithm. This change makes it a lot more like PGIA.
When starting off our N threads, we find N different starting solutions and let the threads go fro…
mhyee updated
10 years ago
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Hi there! Stumbled on AutoOED recently and it looks to be a great fit for what I need. I'm attempting to run a manual experiment and use AutoOED to help guide tuning of parameters. Unfortunately I hav…