Emma Saulnier

TiPS generates trajectories and phylogenetic trees from compartmental models using stochastic simulations and coalescent methods, with an R package for flexible and efficient modeling.

The paper introduces a deep learning method for phylodynamic analysis that outperforms existing approaches on simulated data and applies to HIV outbreak dynamics.

This study evaluates ABC methods for inferring epidemiological parameters from phylogenies, finding comparable or better accuracy than likelihood-based methods for complex models and large datasets.