most citedFinding high posterior density phylogenies by systematically extending a directed acyclic graph

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.PE2025

ARTreeFormer: A Faster Attention-based Autoregressive Model for Phylogenetic Inference

Tianyu Xie, Yicong Mao, Cheng Zhang

Probabilistic modeling over the combinatorially large space of tree topologies remains a central challenge in phylogenetic inference. Previous approaches often necessitate pre-samp…

q-bio.PE2025★ 1 cited

Vector encoding of phylogenetic trees by ordered leaf attachment

Harry Richman, Cheng Zhang, Frederick A. Matsen

As part of work to connect phylogenetics with machine learning, there has been considerable recent interest in vector encodings of phylogenetic trees. We present a simple new "orde…

q-bio.PE2024★ 3 cited

Finding high posterior density phylogenies by systematically extending a directed acyclic graph

Chris Jennings-Shaffer, David H Rich, Matthew Macaulay +7

Bayesian phylogenetics typically estimates a posterior distribution, or aspects thereof, using Markov chain Monte Carlo methods. These methods integrate over tree space by applying…

q-bio.PE2024

Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction

Tianyu Xie, Musu Yuan, Minghua Deng +1

Probability estimation of tree topologies is one of the fundamental tasks in phylogenetic inference. The recently proposed subsplit Bayesian networks (SBNs) provide a powerful prob…

stat.ML2024★ 1 cited

Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions

Tianyu Xie, Frederick A. Matsen, Marc A. Suchard +1

Reconstructing the evolutionary history relating a collection of molecular sequences is the main subject of modern Bayesian phylogenetic inference. However, the commonly used Marko…