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Hello. I am trying to use ChaosPy for uncertainty quantification of a 5 dimensional problem using PCE. The input variables are set to be LogNormal. For one of the variables mean is about 500 and SD is…
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I am interested in discussing and working on ways to quantify and attribute sources of uncertainty in forecasts and ways to communicate these components. There are a wide variety of both model-agnost…
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Sorry to leave message here.
I am interested in your research topic on '[Interaction and Uncertainty-Aware Motion Planning](https://www.diva-portal.org/smash/record.jsf?pid=diva2:1756307)', and I fou…
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Hi all,
The capacity expansion model EMPIRE is a stochastic linear program, and can be classified as a two-stage stochastic program (with a multi-horizon structure). The first-stage decisions inclu…
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Having recently begun the transition from Matlab to Python, Nemos has been a massive help in transferring my Matlab pipelines. Great toolbox!!
I've noticed that Nemos, like other basic modeling pa…
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Hello,
I am trying to conduct PCE for uncertainty quantification for a model that produces time series data. The output is 1200 data points. I am doing UQ with 11 uncertain input parameters, and so…
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After talking with @bartgol at the EESM meeting last week, he suggested making a tracking issue to discuss changes that would be useful or necessary for differentiable modeling, specifically with auto…
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### PyKED/ChemKED version
v0.1.5
Title question suggested by Mike Burke's group at Columbia
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I am pretty intrigued by the [pymt project](https://github.com/csdms/pymt) which also seems to be focused on coupling models, although maybe less focused on inversions/parameter estimation?
Part of…