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cs.PL2026
Compositional Information Geometry of Probabilistic Programs
Jacek Karwowski, Frank Nielsen, Sam Staton
We study the compositional, intensional information geometry of probabilistic programs. For a first-order probabilistic programming language with finite random variables, we constr…
stat.ML2026
LazyHMC: Hamiltonian Monte Carlo Simulation for Lazy, Infinite Dimensional Probabilistic Programs
Maria-Nicoleta Crăciun, C. -H. Luke Ong, Tom Schrijvers +1
Hamiltonian Monte Carlo (HMC) is a successful generic inference method in probabilistic programming, but in its ordinary formulation it needs gradients and finite-dimensional param…