Understanding Popl 26 Probabilistic Programming With Vectorized Programmable Inference
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Key Takeaways about Popl 26 Probabilistic Programming With Vectorized Programmable Inference
- "Speaker: Christopher Fonnesbeck Bayesian statistics offers robust and flexible methods for data analysis that, because they are ...
- Medium-scale automation for proof assistants (Video,
- https://pldi19.sigplan.org/details/pldi-2019-papers/45/Gen-A-General-Purpose-
- Probabilistic programming
- Presented by Hongseok Yang. Presented at
Detailed Analysis of Popl 26 Probabilistic Programming With Vectorized Programmable Inference
Jules Jacobs (Radboud University Nijmegen) Paper: https://dl.acm.org/doi/pdf/10.1145/3434339 Abstract Local Contextual Type So in this talk I'm going to try to propose that we should consider a change to the conceptual model of
The Relative Monadic Metalanguage (Video,
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