Papers Published

1. Zhang, Y; Chen, C; Henao, R; Carin, L, Laplacian Hamiltonian Monte Carlo, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9851 LNAI (January, 2016), pp. 98-114, Springer International Publishing [doi] .
   (last updated on 2024/12/31)

   Abstract:
   We proposed a Hamiltonian Monte Carlo (HMC) method with Laplace kinetic energy, and demonstrate the connection between slice sampling and proposed HMC method in one-dimensional cases. Based on this connection, one can perform slice sampling using a numerical integrator in an HMC fashion. We provide theoretical analysis on the performance of such sampler in several univariate cases. Furthermore, the proposed approach extends the standard HMC by enabling sampling from discrete distributions. We compared our method with standard HMC on both synthetic and real data, and discuss its limitations and potential improvements.