Mind maps are a great way to visually structure the main ideas of an article. I find this particularly useful when I browse more or less difficult articles. Here I share with you some of them. The content of a map is not exhaustive, it corresponds to my reading objective at a given time.
Papers Kuismin and Sillanpaa 2017 Kuismin and Sillanpaa 2017 Estimation of covariance and precision matrix, network structure and a view towards systems biology, M.
I started a Github repository resources-pgm where I will index some interesting resources on probabilistic graphical models. I will update it as I go along. For the moment, it is structured in books, articles and R packages. The content can also be found here.
Contents Books Papers Gaussian graphical models Review Inference Non gaussian graphical models R packages Inference Optimization Variable selection Books Probabilistic Graphical Models, D. Koller and N. Friedman, 2009 Graphical models, S L Lauritzen, 1996 Graphical Models with R, S.