naesseth

nestedsmc

Implementation of various algorithms in the Nested Sequential Monte Carlo family of methods.

smc-pgm

Code implementing sequential Monte Carlo algorithms for probabilistic graphical models described in Naesseth, Lindsten and Schön, "Sequential Monte Carlo for Graphical Models", Advances in Neural Information Processing (NIPS) 27, 2014.

smcpy

Library for Bayesian inference using sequential Monte Carlo (particle filter, condensation, genetic, ...) methods.

pyResampling

An attempt to provide efficient resampling procedures, using Cython, for sequential Monte Carlo type algorithms, also known as particle filters.

scrapers

Lots and lots of web scrapers

academic-kickstart

📝 Easily create a beautiful website using Academic, Hugo, and Netlify

ai-deadlines

:alarm_clock: AI conference deadline countdowns

CSrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

naesseth.github.io

A beautiful, simple, clean, and responsive Jekyll theme for academics

nestedsmcsamplers

old.github.io

old_web

platipus

Thesis implementation of PLATIPUS

pmmh-correlated2015

Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables

smc2d

Code implementing the algorithms described in C. A. Naesseth, F. Lindsten, T B. Schön, Capacity estimation of two-dimensional channels using Sequential Monte Carlo, Proceedings of the 2014 IEEE Information Theory Workshop.

variational-ode