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- 논문에서 얻은 인사이트 정리
- 코드로 구현하는 방법 정리
- 우리꺼에 어떻게 적용할 수 있을지..? 생각하기
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Include new uncertainty quantification feature following Oak Ridge National Lab presentation
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Hi nice paper.
I was wondering from the methods, could you get a quantified number of uncertainty for the model output?
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**Topic**
Uncertainty quantification: How is uncertainty measured, how do you validate it, how is it used?
**How is the topic relevant to the tric-dt themes?**
This topic came up in several conve…
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Given that uncertainty quantification is used often in many settings when confidence in predictions is required it would be nice to include a task in Flaml that tackles this setting.
There are a c…
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https://doi.org/10.1088/0957-0233/24/4/045302 , **page 6 shows the process:**
After image deformation: multiply images, then threshold. White pixels represent particles tht are present in A and B. Us…
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# UQ4ML – Uncertainty Quantification Techniques in Machine Learning Models
This session focuses on uncertainty quantification (UQ) techniques in machine learning models and their applications acros…
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Hi, I recently saw this alternative approach for estimating the uncertainty on the surrogate. Just a heads up, not really an issue.
http://epubs.siam.org/doi/10.1137/130917909
https://github.com/jef…
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Test the code to quantify the uncertainty of the output
- [ ] Run the code repeatedly to get some variance on the output data
...
- [ ] Include the results in the documentation
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This issue can be a collection and discussion of methods we could add to the library at some point, in no particular order :) Feel free to comment with suggestions and if you feel comfortable, you are…