7 citations · 11 across the 3 of their papers we have counts for
3 papers
Torchtree: flexible phylogenetic model development and inference using PyTorch
Mathieu Fourment, Matthew Macaulay, Christiaan J Swanepoel +3
Bayesian inference has predominantly relied on the Markov chain Monte Carlo (MCMC) algorithm for many years. However, MCMC is computationally laborious, especially for complex phyl…
TreeFlow: probabilistic modelling and automatic differentiation for phylogenetics
Christiaan Swanepoel, Mathieu Fourment, Xiang Ji +4
Probabilistic modelling frameworks are powerful tools for statistical modelling and inference. They are not immediately generalizable to phylogenetic problems due to the particular…
Automatic differentiation is no panacea for phylogenetic gradient computation
Mathieu Fourment, Christiaan J. Swanepoel, Jared G. Galloway +4
Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning. These calculations are readily…