3 papers
q-bio.PE2024
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…
q-bio.PE2023
Differentiable Phylogenetics via Hyperbolic Embeddings with Dodonaphy
Matthew Macaulay, Mathieu Fourment
Motivation: Navigating the high dimensional space of discrete trees for phylogenetics presents a challenging problem for tree optimisation. To address this, hyperbolic embeddings o…
stat.CO2023
Many-core algorithms for high-dimensional gradients on phylogenetic trees
Karthik Gangavarapu, Xiang Ji, Guy Baele +4
The rapid growth in genomic pathogen data spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters o…