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#### Summary:
Extend the functionality added in https://github.com/stan-dev/stan/pull/3230 to return the Hessian and the condition number of the Hessian at the end of adaptation.
#### Descript…
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Thanks for this implementation. Recently, I've been working on a package to use machine learning for chemistry problems where I use pytorch to train some models. I have been able to perform distribute…
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### Required prerequisites
- [X] I have searched the [Issue Tracker](https://github.com/OmniSafeAI/omnisafe/issues) and [Discussions](https://github.com/OmniSafeAI/omnisafe/discussions) that this has…
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One crucial thing that public health authorities expect from modelers is to improve control strategies during outbreaks. Then, it would be very useful to combine, within a new package, methods doing r…
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[SGDClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html) is one of the few algorithms that can be used for incremental learning and it would be a grea…
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Any collaborator is most welcome to contribute additional advanced methods to this repository.
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Once #1247 is done, we should consider doing overall optimization around the project. Aim is simply decreasing the huge compilation time, and increasing runtime performance as much as possible.
Thi…
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Consider that I want to come up with an algorithm that optimizes treatment parameters for patients (eg amount & type of medication to take).
Currently if I use algorithms from skopt, I would need …
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There are many planning algorithms that can optimize a path cost with respect to some arbitrary cost function (RRT*, CHOMP, TrajOpt, to name a few). OMPL has a generic path and state cost infrastructu…
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It would be useful to have some more performance metrics for MO optimization.
For instance, some that are often used in MO papers are:
- [ ] Diversity of the non-dominated front
- [ ] Closeness…
Sceki updated
4 years ago