this guy is building a coverage-driven #fuzzer similar to shapr’s effort and similar to the #coverage support in #Hypothesis #PBT
#PDF of #problem-set 8 from MIT #OpenCourseWare “Algorithms for Inference” course, which includes a four-part #particle-filter problem
#OpenCourseWare 6.438 "Algorithms for Inference" #syllabus from 02014: “This is a graduate-level introduction to the principles of statistical inference with probabilistic models defined using graphical representations. The material in this course constitutes a common foundation for work in machine learning, signal processing, artificial intelligence, computer vision, control, and communication. (...) It is worth stressing that 6.438 Algorithms for Inference is an introductory graduate subject: it is not an advanced graduate subject for students who have already have a mastery of statistical inference algorithms, yet want to understand such material at an even more sophisticated level.”
#PDF lecture notes from #OpenCourseWare “Algorithms for Inference” covering, among other things, #particle-filters. There are unfortunately some ESL solecisms in the text.
#OpenCourseWare #PDF slides about #particle-filters, sequential importance sampling, and #MCMC. This is from a different course, not the 02014 6.438 Algorithms for Inference, but 12.S990, “Quantifying Uncertainty”. Though it’s falsely billed as “lecture notes” it’s really PowerPoint thinking, with sequences of bullet points.
The home page for the "Quantifying Uncertainty" #OpenCourseWare course from 02012. No problem sets, no real lecture notes, no recorded lectures.
#tutorial #paper on #particle-filters from 02002 recommended by the “Quantifying Uncertainty” OpenCourseWare course (https://ieeexplore.ieee.org/document/978374) “A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking”, by Arulampalam, Maskell, Gordon, and Clapp
Udacity introductory #video on #particle-filters: “Particle Filters Basic Idea”
another Udacity introductory #video on #particle-filters, with a guy whose accent sounds like Sebastian Thrun’s, with a table of filter types and the video of the robot wandering around a simulated office building
the Udacity #video that explains #particle-filters with pseudocode and a one-dimensional simulated robot
Elfring, Torta, and van de Molengraft’s more comprehensive #particle-filters #tutorial #paper (with #PDF) which supposedly has example code that I can’t find. This is recent (02021) and open-access (#CC BY, I think), and many pages long, and has an overview of a lot of the motivation, but in some sense not very approachable.
linear interpolation for #DSP sample interpolation for fractional-delay filters