Bob Carpenter — accepted AI-conference papers

2025

Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo

AISTATS 2025poster

Hamiltonian Monte Carlo (HMC) is the mainstay of applied Bayesian inference for differentiable models. However, HMC still struggles to sample from hierarchical models that induce densities with multiscale geometry: a large step size is needed to efficiently explore low curvature regions while a smal…

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2025

posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms

Måns Magnusson, Jakob Torgander, Paul-Christian Bürkner, Lu Zhang, Bob Carpenter, Aki Vehtari

AISTATS 2025oral

The general applicability and robustness of posterior inference algorithms is critical to widely used probabilistic programming languages such as Stan, PyMC, Pyro, and Turing.jl. When designing a new inference algorithm, whether it involves Monte Carlo sampling or variational approximation, the fund…

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