2 papers
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…
cs.PL2025
Quantitative Verification of Omega-regular Properties in Probabilistic Programming
Peixin Wang, Jianhao Bai, Min Zhang +1
Probabilistic programming provides a high-level framework for specifying statistical models as executable programs with built-in randomness and conditioning. Existing inference tec…