7 citations · 9 across the 4 of their papers we have counts for
Showing q-bio.PEShow all
2 papers · 1 filter
q-bio.PE2026★ 1 cited
BEAGLE 4.1: A high-performance library for computation on phylogenetic trees across diverse parallel architectures
Karthik Gangavarapu, Xiang Ji, Yucai Shao +4
Efficient evaluation of sequence data likelihoods and their high-dimensional gradients on phylogenetic trees improves inference under both maximum-likelihood and Bayesian framework…
q-bio.PE2022★ 7 cited
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…