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stat.CO2026
Preconditioning Hamiltonian Monte Carlo by minimizing Fisher Divergence
Adrian Seyboldt, Eliot L. Carlson, Bob Carpenter
Although Hamiltonian Monte Carlo (HMC) scales as O(d^(1/4)) in dimension, there is a large constant factor determined by the curvature of the target density. This constant factor c…
stat.CO2025
GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
Nawaf Bou-Rabee, Bob Carpenter, Milo Marsden
We introduce a novel and flexible framework for constructing locally adaptive Hamiltonian Monte Carlo (HMC) samplers by Gibbs sampling the algorithm's tuning parameters conditional…
stat.CO2025
The Within-Orbit Adaptive Leapfrog No-U-Turn Sampler
Nawaf Bou-Rabee, Bob Carpenter, Tore Selland Kleppe +1
Locally adapting parameters within Markov chain Monte Carlo methods while preserving reversibility is notoriously difficult. The success of the No-U-Turn Sampler (NUTS) largely ste…