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Inference with AI (Week 3)

This repo stores all the teaching material for Week 3 of the AI in Science at AIMS programme.

The directories are organised by sessions. Each session directory contains the lecture slides and any accompanying notebooks.

We will add the project material on Wednesday 18th February after the lectures have concluded.

Structure of week

Session 1: Fitting models to data via simulation-based inference

  • Monday 16th February: 14:00 - 15:00
  • Course leader: Callum Gabbutt
  • Course contents

Session 2: Inference with classifiers

  • Monday 16th February: 15:00 - 16:00
  • Course leader: Jon Langford
  • Course contents

Session 3: Bayesian kinetic modeling with hybrid models

  • Tuesday 17th February: 14:00 - 15:00
  • Course leader: Laura Helleckes
  • Course contents

Session 4: Bayesian optimisation for chemistry

  • Tuesday 17th February: 15:00 - 16:00
  • Course leader: Austin Mroz
  • Course contents

Session 5: Bayesian model selection

  • Wednesday 18th February: 14:00 - 15:00
  • Course leader: Lloyd Fung
  • Course contents

Project work

  • Wednesday 18th February: 15:00 - 16:00
    • This hour will include a brief discussion of the project requirements and assessment criteria at the beginning. The marking rubric and slide template are provided below.
    • The project material are in the respective folders for each lecture.
  • Thursday 19th February: 11:00 - 13:00

Project presentations

  • Friday 20th February: 14:15 - 17:00

Project assessment

The project will be assessed based on the criteria in the marking rubric. There are six categories, each worth 1-5 marks (30 total):

  • Visual impact and organisation
  • Verbal presentation and clarity
  • Depth of analysis and future directions
  • Scientific understanding
  • Quality of answers to questions
  • Engagement

The first five categories will be assessed during the presentation. Each project leader will submit their own scores and we will average these to get the final mark. We will score these categories by project group, not by individual, to encourage teamwork and collaboration. However, if a student particularly excels (or underperforms) in one of these categories, we may adjust their mark accordingly.

The final category (engagement) is a continued assessment throughout the project work. This will be decided by the associated course leader.

We have provided a set of template slides for the presentation. These slides can be found in the following google slides link. Please make a copy to start editing. Each student is expected to present at least one slide for an expected length of 2-3 minutes. After the presentation, we will ask one question to each student in the group.

Important - the project presentation should not run over 15 minutes. For each minute over this limit, we will deduct 5% from the final mark. We will stop the presentation at 20 minutes but then you will have lost 25% and no time for questions. Please ensure you rehearse your presentation to fit within the time limit.

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This repo stores all the teaching material for Week 3 of the AI in Science at AIMS programme.

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