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Found 11 papers, 8 papers with code
On the importance of assessing topological convergence in Bayesian phylogenetic inference
Modern phylogenetics research is often performed within a Bayesian framework, using sampling algorithms such as Markov chain Monte Carlo (MCMC) to approximate the posterior distribution.
Random-effects substitution models for phylogenetics via scalable gradient approximations
Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process.
Automatic differentiation is no panacea for phylogenetic gradient computation
Gradients of probabilistic model likelihoods with respect to their parameters are essential for modern computational statistics and machine learning.
Scalable Bayesian divergence time estimation with ratio transformations
Divergence time estimation is crucial to provide temporal signals for dating biologically important events, from species divergence to viral transmissions in space and time.
Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis
Even in the presence of non-trivial phylogenetic model constraints, we show that one may analytically address latent factor uncertainty in a way that (a) aids model flexibility, (b) accelerates computation (by as much as 500-fold) and (c) decreases required tuning.
From viral evolution to spatial contagion: a biologically modulated Hawkes model
Mutations sometimes increase contagiousness for evolving pathogens.
Combining Cox Regressions Across a Heterogeneous Distributed Research Network Facing Small and Zero Counts
Studies of the effects of medical interventions increasingly take place in distributed research settings using data from multiple clinical data sources including electronic health records and administrative claims.
Methodology
Shrinkage with shrunken shoulders: Gibbs sampling shrinkage model posteriors with guaranteed convergence rates
Use of continuous shrinkage priors -- with a "spike" near zero and heavy-tails towards infinity -- is an increasingly popular approach to induce sparsity in parameter estimates.
Methodology Statistics Theory Statistics Theory
Gradients do grow on trees: a linear-time ${\cal O}\hspace{-0.2em}\left( N \right)$-dimensional gradient for statistical phylogenetics
To make this tractable, we present a linear-time algorithm for ${\cal O}\hspace{-0. 2em}\left( N \right)$-dimensional gradient evaluation and apply it to general continuous-time Markov processes of sequence substitution on a phylogenetic tree without a need to assume either stationarity or reversibility.
Computation Populations and Evolution Methodology
Prior-preconditioned conjugate gradient method for accelerated Gibbs sampling in "large $n$ & large $p$" Bayesian sparse regression
We can then solve the linear system by the conjugate gradient (CG) algorithm through matrix-vector multiplications by $\Phi$; this involves no explicit factorization or calculation of $\Phi$ itself.
Spatio-temporal Dynamics of Foot-and-Mouth Disease Virus in South America
Although foot-and-mouth disease virus (FMDV) incidence has decreased in South America over the last years, the pathogen still circulates in the region and the risk of re-emergence in previously FMDV-free areas is a veterinary public health concern.
