Evolutionary BiologyPLoS Computational BiologyPeer-reviewed
Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models
Yucai Shao, Andrew F. Magee, Tetyana I. Vasylyeva, Marc A. Suchard
This paper introduces a gradient-based Hamiltonian Monte Carlo sampler for efficient inference in episodic birth-death-sampling models, showing significant computational improvements over Metropolis-Hastings methods.
6 citations