PofoliaShared via Pofolia

arXiv (Cornell University)· 2014· Preprint

The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo

Matthew D. Homan, Andrew Gelman

Short summary

The No-U-Turn Sampler (NUTS) eliminates the need to manually set the number of steps (L) in Hamiltonian Monte Carlo (HMC) by automatically determining an optimal path length, performing comparably to or better than tuned HMC without user intervention.

AI-generated from the title and abstract; the full text is not read.

TakeawaysIn the app
Key pointsIn the app
Ask the paperIn the app

The rest is in the Pofolia app

Takeaways, key points and questions to the paper; new summaries every day for your field. Free.

Sign in on the web to open

Field: Statistics and Probability

Statistics and ProbabilityMathematics