WRSWorld Research StateContribute
WORLD RESEARCH STATE

No-U-Turn Sampler adaptive HMC trajectory lengths

Contribution grade

Bayesian computation · Human-designed research method or resource

Reference score310,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Adapts Hamiltonian trajectory lengths using a recursively doubled candidate tree and no-U-turn stopping construction, with dual-averaging step-size adaptation.

Scientific scope

Adapts Hamiltonian trajectory lengths using a recursively doubled candidate tree and no-U-turn stopping construction, with dual-averaging step-size adaptation. The reversible candidate-selection construction matters: merely stopping a trajectory at its first U-turn is explicitly not justified. HMC, slice sampling and dual averaging are inherited. Removes selected hand-tuned parameters, not all choices, diagnostics or finite-chain convergence risk;2011preprint not2014journal body.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. The reversible candidate-selection construction matters: merely stopping a trajectory at its first U-turn is explicitly not justified. HMC, slice sampling and dual averaging are inherited. Removes selected hand-tuned parameters, not all choices, diagnostics or finite-chain convergence risk;2011preprint not2014journal body.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

Full scientific record · Browse contribution grades · Request a correction