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Implement Weibull distribution #59
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One clean way to implement this would be via |
I'll look into the Bijector, but there's other type of abstractions available. For example for the continuous weibull; |
To clarify we don't yet have Bijejctors in torch.distributions 😄 I'm just trying to gather evidence that Bijectors would simplify lots of things. I didn't realize you were implementing Discrete Weibull; Bijectors will only handle continuous distributions. |
@ragulpr Are you implementing the Weibull distribution? |
Yes, I just started |
Is it urgent? I haven't been able to keep up with the latest API and my implementation is slightly behind, or ahead I'm not sure. |
Oh no, it wasn't urgent. Sorry if I made it sound that way. I just was looking at a possible simplistic continuous Weibull distribution using existing transforms. I also very recently realized that the discrete Weibull is a bit harder to do too. |
I'm looking into it! Will ask questions on slack 👍 |
Great work everyone. I'm planning on implementing the Weibull distribution for pytorch anyways, is there any interest in merging this here?
I just wanted to give a heads up if someone else is thinking about it. I can give details about the timeline after consulting with my lab.
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