No-U-Turn Sampler
E898983
The No-U-Turn Sampler is an adaptive variant of Hamiltonian Monte Carlo that automatically tunes trajectory lengths to efficiently explore complex probability distributions without manual parameter selection.
All labels observed (1)
| Label | Occurrences |
|---|---|
| No-U-Turn Sampler canonical | 6 |
How this entity was disambiguated
This entity first appeared as the object of triple T11002324 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: No-U-Turn Sampler Context triple: [Hamiltonian Monte Carlo, generalization, No-U-Turn Sampler]
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A.
Toinette
Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
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B.
The Roller
"The Roller" is a 2011 rock single by English band Beady Eye, noted for its Beatlesque sound and status as one of the group's best-known songs.
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C.
Monte Carlo
Monte Carlo is a famous district of Monaco renowned for its luxury casinos, upscale resorts, and role as a glamorous hub for high-end tourism and events like the Monaco Grand Prix.
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D.
Ripcord
"Ripcord" is a song by the English rock band Radiohead, featured on their 1993 debut album Pablo Honey.
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E.
Touchstone
Touchstone is a publishing imprint known for releasing a wide range of commercial fiction and nonfiction titles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: No-U-Turn Sampler Target entity description: The No-U-Turn Sampler is an adaptive variant of Hamiltonian Monte Carlo that automatically tunes trajectory lengths to efficiently explore complex probability distributions without manual parameter selection.
-
A.
Toinette
Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
-
B.
The Roller
"The Roller" is a 2011 rock single by English band Beady Eye, noted for its Beatlesque sound and status as one of the group's best-known songs.
-
C.
Monte Carlo
Monte Carlo is a famous district of Monaco renowned for its luxury casinos, upscale resorts, and role as a glamorous hub for high-end tourism and events like the Monaco Grand Prix.
-
D.
Ripcord
"Ripcord" is a song by the English rock band Radiohead, featured on their 1993 debut album Pablo Honey.
-
E.
Touchstone
Touchstone is a publishing imprint known for releasing a wide range of commercial fiction and nonfiction titles.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
Hamiltonian Monte Carlo variant
ⓘ
Markov chain Monte Carlo algorithm ⓘ adaptive MCMC method ⓘ |
| abbreviation | NUTS ⓘ |
| advantageOver | standard HMC with fixed trajectory length ⓘ |
| aimsTo |
efficiently explore complex probability distributions
ⓘ
improve mixing of Markov chains ⓘ improve sampling efficiency ⓘ reduce random walk behavior in MCMC ⓘ |
| assumes | ability to compute gradients of log posterior ⓘ |
| basedOn | Hamiltonian Monte Carlo ⓘ |
| category | gradient-based MCMC method ⓘ |
| comparedTo | standard Hamiltonian Monte Carlo ⓘ |
| field |
Bayesian statistics
ⓘ
computational statistics ⓘ machine learning ⓘ |
| fullName | No-U-Turn Sampler ⓘ |
| hasComponent |
U-turn stopping rule
ⓘ
step size adaptation procedure ⓘ tree-building procedure ⓘ |
| hasFeature |
adaptive trajectory length
ⓘ
automatic tuning of path length ⓘ dynamic integration time ⓘ no manual number of leapfrog steps selection ⓘ no manual trajectory length selection ⓘ stopping criterion based on U-turn detection ⓘ |
| hasVariant |
NUTS with dual averaging step size adaptation
ⓘ
linked to:
Hamiltonian Monte Carlo
|
| implementedIn |
NumPyro
ⓘ
PyMC ⓘ
linked to:
PyMC3
Stan ⓘ TensorFlow Probability ⓘ
linked to:
TensorFlow Probability (JAX backend)
Turing.jl ⓘ
linked to:
Julia
|
| introducedBy |
Andrew Gelman
ⓘ
Matthew D. Hoffman ⓘ |
| introducedInPublication | No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo ⓘ |
| property |
maintains detailed balance
ⓘ
produces asymptotically exact samples under regularity conditions ⓘ reduces need for manual tuning compared to basic HMC ⓘ suitable for high-dimensional parameter spaces ⓘ uses gradient information of log posterior ⓘ |
| publicationYear | 2011 ⓘ |
| requires | differentiable log density ⓘ |
| targetDistribution | continuous probability distributions ⓘ |
| usedFor |
Bayesian posterior inference
ⓘ
hierarchical Bayesian models ⓘ probabilistic modeling ⓘ sampling from posterior distributions ⓘ |
| uses |
Hamiltonian dynamics
ⓘ
leapfrog integrator ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: No-U-Turn Sampler Description of subject: The No-U-Turn Sampler is an adaptive variant of Hamiltonian Monte Carlo that automatically tunes trajectory lengths to efficiently explore complex probability distributions without manual parameter selection.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.