Blog

Conditional Random Field, the factor graph representation

Maximize Likelihood / Maximize Entropy duality

Rao-Blackwellization in Particle Filter

EKF-SLAM hands-on tutorial

A robot wanders into the asterisk forest

Gaussian process regression

Representation - Bayesian Networks

Course Note Probabilistic Graphical Models (by Daphne Koller)

Sparse Extended Information Filter

Course Note SLAM (by Cyrill Stachniss)

Extended Information Filter

Course Note SLAM (by Cyrill Stachniss)

Unscent Kalman Filter

Course Note SLAM (by Cyrill Stachniss)

EKF SLAM

Course Note SLAM (by Cyrill Stachniss)

Extended Kalman Filter

Course Note SLAM (by Cyrill Stachniss)

Introduction to Bayes Filter

Course Note SLAM (by Cyrill Stachniss)

Homogeneous coordinates

Course Note SLAM (by Cyrill Stachniss)

Introduction to SLAM

Course Note SLAM (Cyrill Stachniss)

Optimizers

Caffe Initializers

Objective and loss functions

Introduction to Bayesian inference