Seong-Hwan Jun, Hassan Nasif, Chris Jennings-Shaffer, David H Rich, Anna Kooperberg, Mathieu Fourment, Cheng Zhang, Marc A Suchard, Frederick A Matsen
Bayesian phylogenetics is a computationally challenging inferential problem. Classical methods are based on random-walk Markov chain Monte Carlo (MCMC), where random proposals are made on the tree parameter and the continuous parameters simultaneously. Variational phylogenetics is a promising alternative to MCMC, in which one fits an approximating distribution to the unnormalized phylogenetic posterior. Previous work fit this variational approximation using stochastic gradient descent, which is the canonical way of fitting general variational approximations...
July 31, 2023: Algorithms for Molecular Biology: AMB