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## š Bug
The Poisson distribution is a discrete distribution. As is the case with all other discrete distributions: `bernoulli` and `multinomial`, `torch.poisson` should also return a tensor with dā¦
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# Flexible conditional density estimators for discrete data
Neural conditional density estimators such as MDNs and MAFs are great for continuous data, but often we run into discrete distributions (ā¦
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If we only observe discretized `endog` for an underlying continuous distribution, then we can use MLE with the pmf based on the bins, `diff(cdf(bin_edges))`.
This is relatively easy to do for distribā¦
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```julia
julia> logpdf(KSOneSided(1), 0.5)
ERROR: MethodError: no method matching pdf(::KSOneSided, ::Float64)
Closest candidates are:
pdf(::Chernoff, ::Real) at C:\Users\user\.julia\packages\Diā¦
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Hey!
I am trying to do VI with models involving discrete RVs. For that purpose it would be quite handy to get derivative estimators for PMFs of Bernoulli (and other discrete) RVs. Considering the fā¦
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In particular, it could help both best-first enumeration and sampling algorithms if we sort the support of discrete distributions such that higher-probability values come first.
For other ideas, see ā¦
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I revised the higher order probabilism paper revised *up to section 4 only*. I incorporated most of Rafal's replies in #95 to the reviewers:
Please check whether the revisions are acceptable. (Filā¦
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this has very good overview notes, including Dvoretzky-Kiefer-Wolfowitz simultaneous confidence band and pointwise confint_proportion confidence intervals
it looks like both should apply to both discā¦
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The docstring simply states:
```
pdf(d::UnivariateDistribution, x::Real)
Evaluate the probability density (mass) at x.
```
This surely isn't enough to know when it returns density, and whenā¦
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**Reference**: https://stackoverflow.com/questions/56189110/is-there-a-compound-distribution-in-sympy-for-discrete-finite-random-variables
I am not sure if such distributions have been implemented.ā¦