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Schedule and course plan

Period 2

Where and when Activity Reading Examination

Tue 3 Nov

10:15-12:00

M1

Lecture 1: Introduction

Hedvig Kjellström

Bishop 1

Bishop 2, use as a math reference all through the course

Wed 4 Nov

10.15-12.00

M1

Lecture 2: Regression

Python Code

Carl Henrik Ek

Bishop 6.4

Thu 5 Nov

13.15-15.00

M2

Lecture 3: Gaussian Processes

Python Code

Carl Henrik Ek

Bishop 6.4

Fri 6 Nov

15.15-17.00

V1

Exercise 1: Derivations

Carl Henrik Ek

Wed 11 Nov

10.15-12.00

V3

Lecture 4: Representation Learning

Carl Henrik Ek

Bishop 12.2, 12.4

Thu 12 Nov

13.15-15.00

L1

Lecture 5: Approximative Inference

Carl Henrik Ek

Bishop 6.4.6, 10.1, 10.2

Bishop 10.3, optional

Fri 13 Nov

15.15-19.00

V1

Exercise 2-3: Variational Bayes

Carl Henrik Ek

Tue 17 Nov

10.15-12.00

D3

Lecture 6: Graphical Models

Jens Lagergren

Bishop 8.1-8.3

Wed 18 Nov

10.15-12.00

V22 (small room)

Lecture 7: Graphical Models contd, Hidden Markov Models

Jens Lagergren

Bishop 13.1, 13.2.1, 13.2.2, 13.2.5, 13.2.6

Thu 19 Nov

Hand-in 12.00 NOON

Results on Monday 23 nov

Reading, slides from Lectures 2-5 Assignment 1

Tue 24 Nov

10.15-12.00

B1

Lecture 8: Expectation-Maximization Applied to Hidden Markov Models

Slides & notes.

Jens Lagergren

Bishop 9.1-9.3

Wed 25 Nov

10.15-12.00

E3

Lecture 9: Expectation-Maximization contd

Jens Lagergren

Slides & notes.

Thu 26 Nov

13.15-15.00

B3

Exercise 4: Lectures 6-9

Jens Lagergren

Training HMMs in more detail

Fri 27 Nov

15.15-17.00

E3

Lecture 10: Non-Gaussian and Discrete Latent Variable Models

Hedvig Kjellström

Bishop 8.2.2, 12.4.1

Hyvärinen and Oja

Tue 1 Dec

10.15-12.00

M2

Lecture 11: Bag of Words, Topic Models

Hedvig Kjellström

Blei and Lafferty

Wed 2 Dec

10.15-12.00

K2

Exercise 5: Probabilistic Independent Component Analysis

Whiteboard photos: 1 2 3 4 5 6 7

Hedvig Kjellström

Beckmann and Smith, optional

Thu 3 Dec

13.15-15.00

L51 (small room)

Lecture 12: Sampling

Hedvig Kjellström

Bishop 11.1-11.3

Griffiths

Fri 4 Dec

15.15-17.00

E3

Lecture 13: The Structure of a Scientific Paper

Hedvig Kjellström

Allen

Duvenaud et al.

Tue 8 Dec

12.00-13.00

Room 1448, Lindstedtsv 3 floor 4

Help session about Assignment 2, Task 2.1-2.4

Jens Lagergren

Tue 15 Dec

10.15-12.00

K2

Exercise 6: Lecture 12, Assignment 2

Hedvig Kjellström

Wed 16 Dec

Hand-in 12.00 NOON

Results on Friday 18 dec

Reading, slides from Lectures 6-12 Assignment 2

Mon 18 Jan

14.00-18.00

E52 (small room)

Hand-in 12.00 NOON

Oral project presentations, 10 min per project group, SCHEDULE TBD

Paper, slides from Lecture 13
Project