faster HMC by learning

Just received the good news that our paper Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale by Wu Changye (吴昌烨), Pierre Pudlo, Julien Stoehr and myself, got accepted in Statistics & Computing! This is great in its own, but further concludes a story that started with Changye’s PhD thesis at Paris Dauphine in 2018, with a revision request from Statistics & Computing that stalled with Changye’s departing for industry in Shanghai and eventually resumed thanks to Julien’s massive investment in coding and improving the learning mechanism. It may also conclude my story with Statistics & Computing, where I am supposed to be the historically most prolific author (?), given the move by Springer to a cash-flow model on 01 January, 2027…