Интеллектуальный анализ данных (О.Ю. Бахтеев, В.В. Стрижов)/Осень 2022
Материал из MachineLearning.
Each Saturday 13:10 at the channel m1p.org/go_zoom
Intelligent data analysis
This course develops skills of communication. The goal is to deliver your message to wide auditory of professionals. The form of delivery is a short paper. It results several discussions in our team according to the plan below.
Schedule and grading
Workflow
- Select topic (report)
- Prepare material (present 5-10 min and discuss)
- Make presentation (20 min and questions)
- Write your text (2 pages and discuss)
- Publish your text (link)
Calendar
- Sep: 16, 23, 30 select
- Oct: 7, 14, 21, 28 talk
- Nov: 4, 11 talk, 18, 25 text
- Dec: 2 link, 9 fin
Insert your name and direct link to materials. Each column must carry your name.
| Date | Select | Talk | Text |
|---|---|---|---|
| 16nxt | Islamov, Strijov | ||
| 23sep | ... | ||
| 30 | ... | ||
| 7oct | x | ... | |
| 14 | ... | ||
| 21 | ... | ||
| 28 | ... | ||
| 4nov | ... | ||
| 11 | ... | ||
| 18 | x | ... | |
| 25 | x | ... |
Course page, and projects
- TODO Course page
- TODO Project folder
The result links before 2nd of december
- Bronstein, M. Temporal Graph Networks, Medium TDS
- Your name
Topics to discuss
- Differential alignment of continuous-time (series) videos [2104.13478]
- Taken's theorem and convergent cross-mapping (signals) [or 2208.10981]
- Graph diffusion models with PDE examples (flows, signals,videos) [2106.10934]
- or probabilistic diffusion models [2208.11970]
- Dimensionality reduction on Riemannian manifolds (for videos) [1605.06182]
- Applications of Lagrangian, Hamiltonian and Noetherian neural PDEs [colab Severilov] [or 2208.06120]
