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Hello there, there are a few other approaches to this that I have seen and wondered if they are on your radar.
Bellman Conformal Inference (BCI) - optimises prediction intervals for time series …
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While the design philosophy of this library is generally to frame causal computations as probabilistic ones, Pyro is a sufficiently rich foundation that other algorithmic approaches to causal inferenc…
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Stan is a probabilistic programming language. I will be discussing a bit about what is "Bayesian Inference" and demonstrate some examples using Stan.
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hello, Could you provide visuliaztion code generating Fig6 in the paper
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### Title:
Improving Entrepreneurial Decision Making with Bayesian Reasoning and Intelligent Assistance Distribution channel: Salesforce app exchange platform
### Pain Point:
Addresses the com…
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Need some help.
[InferNet_2019.zip](https://github.com/dotnet/infer/files/3000183/InferNet_2019.zip)
I converted the DifficultyAbility.cs code from C# to F#. But, I am getting the exception "Mic…
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I'm going to log my activities regarding probabilistic programming languages on this issue page.
This will lead to a new BNN model using a more powerful Python library, i.e. **Pyro**.
I'll also put…
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I tried to experiment with approximate counting (FACT algorithm) using the commands below.
java -cp boostsrl_v1.1.1.jar edu.wisc.cs.will.Boosting.MLN.RunBoostedMLN -l -train train/ -target (target)…
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~~Blocked for now by #51~~ We may also need a `TruncatedNormal` distribution.
This issue proposes to add versions of the examples in section 6 from [Discrete-Continuous Mixtures in Probabilistic P…
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Thank you for sharing your code. During inference, when we obtain the pose distribution p(y|X) by the probabilistic PnP layer, how to use the p(y|X) to obtain the y*? We can not understand the Sectio…