7 citations · 21 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
Computational Statistics and Data Science in the Twenty-first Century
Andrew J. Holbrook, Akihiko Nishimura, Xiang Ji +1
Data science has arrived, and computational statistics is its engine. As the scale and complexity of scientific and industrial data grow, the discipline of computational statistics…
Massive Parallelization of Massive Sample-size Survival Analysis
Jianxiao Yang, Martijn J. Schuemie, Xiang Ji +1
Large-scale observational health databases are increasingly popular for conducting comparative effectiveness and safety studies of medical products. However, increasing number of p…
Accelerating Bayesian inference of dependency between complex biological traits
Zhenyu Zhang, Akihiko Nishimura, Nídia S. Trovão +5
Inferring dependencies between complex biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible wh…