Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
This is a page not in th emain menu
Courses and Teaching
This is a page not in th emain menu
Boyang's Home Page
Home Page
Posts
Genetic LLM Evo: A Third-Party Perspective
Published:
Learning biological patterns is hard, even for large language models. Learning meaningful biology at the genetic level? That’s even harder. Yet, a recently proposed LLM, Evo, asks the bold question: Is DNA all you need?
Expectation-Maximization (EM) algorithm part II (EM-PCA)
Published:
In this section, we will explore another practical application of the EM-algorithm to speed up the computation of PCA. This section assumes the readers have already read my introduction part of EM algorithm.
Expectation-Maximization (EM) algorithm part I (Introduction)
Published:
Introduction
Maximum likelihood estimation (MLE) is a way of estimating the parameters of a statistic model given observation. It is conducted to find the parameters that maximize observations’ likelihood under certain model distribution assumptions. However, in many real life problems, we are dealing with problems with parameters that are not directly available to infer given the limited data we have, which are called hidden variables Z. Many problems in the areas of genomics involve dealing with hidden variables. Typical examples in genomics are (i) inferring microbial communities (Z: different communities) (ii) inferring the ancestries of a group of individuals (Z: different ancestries) (iii) inferring the cell type content from specific sequencing data (Z: different cell types). Problems involving hidden variables like these are typically hard to directly performing maximum likelihood estimation.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2 
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.