glouppe/info8010-deep-learning
Lectures for INFO8010 - Deep Learning, ULige
| repo name | glouppe/info8010-deep-learning |
| repo link | https://github.com/glouppe/info8010-deep-learning |
| homepage | |
| language | Jupyter Notebook |
| size (curr.) | 435102 kB |
| stars (curr.) | 328 |
| created | 2018-03-14 |
| license | BSD 3-Clause “New” or “Revised” License |
INFO8010 - Deep Learning
Lectures for INFO8010 - Deep Learning, ULiège, Spring 2020.
- Instructor: Gilles Louppe (g.louppe@uliege.be)
- Teaching assistants: Matthia Sabatelli (m.sabatelli@uliege.be), Antoine Wehenkel (antoine.wehenkel@uliege.be)
- When: Spring 2020, Friday
8:30AM9:00AM - Classroom:
B28/R3lectures are now virtual.
Agenda
| Date | Topic |
|---|---|
| February 7 | Outline [PDF]Lecture 0: Introduction [PDF]Lecture 1: Fundamentals of machine learning [PDF]Tutorial 1: Installation and tensor operations |
| February 14 | Lecture 2: Neural networks [PDF]Tutorial 2: Using pre-trained neural networks |
| February 21 | Lecture 3: Convolutional networks [PDF]Tutorial 3: Backpropagation |
| February 28 | Lecture 4: Computer vision [PDF]Q&A session |
| March 6 | Lecture 5: Training neural networks [PDF]Tutorial 4: Neural networks with PyTorch Project proposal |
| March 13 | |
| March 20 | Lecture 6: Recurrent neural networks [PDF] |
| March 27 | Lecture 7: Auto-encoders and generative models |
| April 3 | Lecture 8: Generative adversarial networksReading assignment |
| April 24 | Lecture 9: Attention and transformer networksQ&A session |
| May 1 | Project code and report |
| May 8 | Lecture 10: Uncertainty |
| May 15 | Lecture 11: TBD |
Project
See instructions in project.md.
Reading assignment
Your task is to read and summarize a major scientific paper in the field of deep learning. You are free to select one among the following three papers:
You should produce a report that summarizes the problem that is tackled by the paper and explains why it is challenging or important. The report should outline the main contributions and results with respect to the problem that is addressed. It should also include a critical discussion of the advantages and shortcomings of the contributions of the paper.
Constraints:
- You can work in groups of maximum 3 students.
- You report must be written in English.
- 2 pages (excluding references, if any).
- Formatted using the LaTeX template
template-report.tex.
Your report should be submitted by April 3, 2020 at 23:59 on the submission platform. This is a hard deadline.
