ConvNet Architecture 2

09-29

Parameter Learning with Complete Data

09-16

ConvNet Architecture 1

09-15

Factor Graph and the Junction Tree Algorithm

09-09

Convolution and Pooling

09-08

Variable Elimination and Belief Propagation

09-02

Training Deep Networks

09-01

Markov Random Fields (Undirected Graphical Models)

08-26

From Shallow to Deep Neural Network

08-25

Bayesian Networks (Directed Graphical Models)

08-19