Probability Distributions, Sampling methods, Variational Bayesian Methods, Deep Learning, HMM’s, Graphical Models,  Applications

QIS/LSF Link:

https://qis.server.uni-frankfurt.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=223191&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung

Lecture: Wednesday 16:00-18:00, SR307

Tutorial & problem session: Wednesday  `14:00-16:00, SR11

Written exam: will be ORAL

Schedule:

• Foundations – Nils Bertschinger ( 8 to 9 weeks )
• Additional algorithms, applications –  Ramesh ( Rest of the weeks )

Applications Lecture 1:  June 28,  MachineLearningPart2_Lec1_Applications

Exercise 10 (July 5 – July 12): ex10  image_small.png

Applications Lecture 2:  July 5,  Prince book slides – Graphical Models  ( 11_Models_For_Chains_And_Trees 10_Graphical_Models )

Applications Lecture 3:  July 12  Graphical Models, EM, Variational Inference ( MachineLearningPart2_Lec3_4_EM_VB )