Main Page
October 25th — Deadline for the conference abstracts.
Each Tuesday at 16:10 — the lecture MMF at m1p.org/go_zoom
September 7th — Mathematical methods of forecasting starts, see youtube MachineLearningPhystech
June 22th — the student talks on research results BS theses
June 15th — the student talks on research results MS theses
April 28th — the student talks on research results 3rd year
Contents
Mathematical methods of forecasting, Fall 2022
This course delivers methods of model selection in machine learning and forecasting. The modeling data are videos, audios, encephalograms, fMRIs and another measurements in natural science. The models are linear, tensor, deep neural networks, and neural ODEs. The practical examples are brain-computer interfaces, weather forecasting and various spatial-time series forecasting. The lab works are organized as paper-with-code reports. See course page
My first scientific paper, Spring 2023
This course produces student research papers. It gathers research teams. Each team joins a student, a consultant, and an expert. The student is a project driver who wants to plunge into scientific research activities. The graduate student consultant conducts the research and helps the student. The expert, a professor, states the problem and enlightens the road to the goal. The projects start in February and end in May 2023, according to the schedule.
- Course schedule
- Week 0: Come in
- Week 1: Set the toolbox
- Week 2: Select your project and tell about it
- Week 3: State your problem
- Week 4: Plan the experiment
- Week 5: Visualise the principle
- Week 6: Write the theory
- Week 7: Analyse the error
- Week 8: Construct your paper
- Week 9: Review a paper
- Week 10: Select a journal to submit
- Week 11: Prepare your presentation
- Week 12: Show your results (Youtube)
Links
- 2022 results GitHub
- Telegram: discussion Ask here!
- The meeting room: m1p.org/go_zoom
- More courses from the MIPT Intelligent Systems
History
- Main page with old homework
- Group 674, 694, spring 2020
- Group 674, spring 2019
- Group 694, spring 2019