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Hi!
Are you going to add functionality for the interpretation of GNN models to torchdrug?
There are benchmarks datasets [Benchmarks for interpretation of QSAR models](https://jcheminf.biomedcent…
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Currently we can only model open-loop models, i.e. models that terminate with prescribed distal boundary conditions (like a distal pressure). I am adding the following:
- A heart/pulmonary circulat…
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Hello,
I am the maintainer of an uncertainty quantification library [chaospy](https://github.com/jonathf/chaospy).
A user of my software has asked a question about using chaospy to do so kalled Po…
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Hi Lingkai !
Thanks for your fantastic paper. I want to consult some questions if possible.
(1) Which strategy does this network operate:
- Strategy 1
-Input Image → DNN → Output + Unc…
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Problem: XGBoost is a great library, but it currently lacks reliable modern uncertainty quantification that is rather easy to implement using conformal prediction. https://github.com/valeman/awesome-…
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Since we already have the functionality to compute and store many profiles per parameter, we have everything at hand to implement a profile merger.
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Hi @Jianguo99,
I am new to conformal prediction, and I have a multitask, multi-output model that performs both classification and regression for a specific problem. Is it possible to use this kind …
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Hi ,
I have installed all the dependencies for pi3nn code:
--- python (>=3.8, version 3.8.3 is used in this study)
--- TensorFlow (>=2.0, version 2.4.1 is used in this study)
--- Hyperopt (=0.2.5…
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Hello Hugh,
i come again to discuss with you another subject around the doubly stochastic DGP.
When predicting using the doubly stochastic DGP you suggest a Gaussian mixture of the variational pos…
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I would like to get the standard error of predictions from a random forest trained on `y=log(x+1)` target. The `var.hat` returned by _randomForestInfJack_ is the variance of `y`, so `se=sqrt(var.hat)`…