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**Submitting author:** @thierrymoudiki (Thierry Moudiki)
**Repository:** https://github.com/Techtonique/ahead
**Branch with paper.md** (empty if default branch): paper
**Version:** v0.11.0
**Editor:**…
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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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I mentionned an issue I had using the library to assess the uncertainty of my DAE system solution on the forum :
https://discourse.julialang.org/t/problem-understanding-results-of-diffequncertaint…
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**Is your feature request related to a problem? Please describe.**
Conformal Prediction is a powerful uncertainty quantification framework that can benefit multiple stages of Twitter algorithm
**D…
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@ppdebreuck @ml-evs,
Really enjoyed reading the [J. Phys paper](https://iopscience.iop.org/article/10.1088/1361-648X/ac1280). Very thorough and timely contribution! I'm curious if you know of or ha…
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I'm excited by the prospect of uncertainty quantification via conformal prediction that has been implemented. I noticed that it can do quantiles and prediction intervals in the current state. Would it…
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## Is your feature request related to a problem? Please describe.
There is currently no built-in way of assessing the volatility or uncertainty associated with metrics generated via `MetricFrame`…
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Hi, I wonder if Multi-fidelity neural network with uncertainty quantification can be implemented as below:
dropout_rate = 0.01
net = dde.nn.MfNN(
[4] + [20] * 4 + [1],
[20] * 3 + [1],
…
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Did a quick search, and it seems like some [additional dropout functionality related to quantifying model uncertainty was added](https://github.com/materialsvirtuallab/megnet/pull/8), but I don't thin…