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
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: Sphere Point Picking. Foll
I. Taylor, and A. Turing. (2015)cite arxiv:1505.04715Comment: This update re-formats two figures to give a closer representation of the underlying text. The original paper is available from the National Archives in the UK at www.nationalarchives.gov.uk using reference number HW 25/38. 4 pages, two column format, complete text of original paper.
I. Taylor, and A. Turing. cite arxiv:1505.04714Comment: This version re-formats two figures to give a closer representation of Turing's original text - available from the National Archives in the UK at www.nationalarchives.gov.uk using reference number HW 25/37. Editor's notes in this document notes apply to both papers. 33 pages (vi + 27), Editors Notes, 7 Figures, Tables, complete text of original Alan Turing paper.(2015)
A. Gibbs, and F. Su. (2002)cite arxiv:math/0209021Comment: To appear, International Statistical Review. Related work at http://www.math.hmc.edu/~su/papers.html.
C. Canonne. (2020)cite arxiv:2002.11457Comment: This is a review article; its intent is not to provide new results, but instead to gather known (and useful) ones, along with their proofs, in a single convenient location.