The death rate for Nipah virus is up to 75% and it has no vaccine. While the world focuses on Covid-19, scientists are working hard to ensure it doesn't cause the next pandemic.
Turning procedural and structural knowledge into programs has established methodologies, but what about turning knowledge into probabilistic models? I explore a few examples of what such a process could look like.
While implementing a quick toy example of Crane and Sawhney's really great Monte Carlo Geometry Processing paper, the question arose about whether a quick function I grabbed from The Internet to equally distribute points on a sphere was correct or not. Since it's absolutely the crux of the method, this is an important question! This notebook performs a rather unscientific check for equal distribution of points on the surface of a sphere. It uses the first algorithm from MathWorld
Importance of Unpaywall free browser extension for finding accessible versions of journal articles via dblp. dblp is a German-funded (but English readable) computer science bibliography that provides more than 5 million hyperlinks for research publications.
Special Collection for COVID-19; Note that last link in section 'other theme issues in this area' is 'Opening the black box: re-examining the ecology and evolution of parasite transmission'
A [personal]<-[notebook]->[network]. Complete with custom numerics for constrained Gaussian gravitation physics.
"Sursis is a web app built on top of Streamlit ... Its basic purpose is to have a personal notebook or journal to jot down ideas, movies or records you have recently enjoyed or pieces of information related to personal projects. The particular conceit of Sursis is that this journal is not written sequentially, but as a network/graph. (It's been recently compared to mind-mapping, but without exception every such tool seems to expect you to figure out a tree-like outline. Sursis is much, much more general if that's the comparison to be made). Sursis runs locally."
Reminds me of PearlTrees ...