Sequential Monte Carlo methods for Bayesian Phylogenetic Inference-tengbo9885手机版客户端大学tengbo9885手机版客户端系

Sequential Monte Carlo methods for Bayesian Phylogenetic Inference
主讲人 Shijia Wang 主讲人简介 <p>Shijia Wang is an associate professor in School of Statistics and Data Science, Nankai University, where he has been a faculty member since 2019. Before that, he received his PhD in statistics at Simon Fraser University, Canada. His research interest involves computational statistics, statistical machine learning and computational biology. He has published papers in statistical journals and machine learning conferences, including Journal of Computational and Graphical Statistics, Systematic Biology, Advances in Neural Information Processing Systems and Bioinformatics.&nbsp;</p>
主持人 Weixuan Zhu 简介 <p>Phylogenetic tree reconstruction is a main task in evolutionary biology. Traditional MCMC methods may suffer from the curse of dimensionality and the local-trap problem. Sequential Monte Carlo methods have emerged as alternatives to MCMC methods for phylogenetic reconstruction. Firstly, we introduce a new combinatorial SMC method, with a novel and efficient proposal distribution. We also explore combining SMC and Gibbs sampling to jointly estimate the phylogenetic trees and evolutionary parameter of genetic datasets. Secondly, we propose an&ldquo;embarrassingly parallel&rdquo;method for Bayesian phylogenetic inference, annealed SMC, based on recent advances in the SMC literature such as adaptive determination of annealing parameters.</p>
时间 2022-10-26(Wednesday)16:40-18:00 地点 Room N402, Economics Building
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联系人信息 许老师,电话:0592-2182991,邮箱 讲座语言 English
期数 高级计量腾博官网诚信为本客服下载学与统计学系列讲座2022年秋季学期第三讲(总147讲)