Nonparametric Hamiltonian Monte Carlo
Probabilistic programming uses programs to express generative models whose posterior probability is then computed by built-in inference engines. A challenging goal is to develop general purpose inference algorithms that work out-of-the-box for arbitrary programs in a universal probabilistic programm...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2021
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