List of lectures

This is a tentative list of the planned lectures for CCS 2021-2022.

1. 21 September: Introduction (ccs_l01_intro.tex)
2. 23 September: Model building (ccs_l02_modelbuilding.md)
3. 28 September: Parameters and probabilities 1 (ccs_l03_parameters.md)
4. 30 September: Parameters and probabilities 2 (ccs_l04_paramsProbs.md)
5. 05 October: Parameters and Probabilitys 3 (ccs_l05_probs2.md)
6. 07 October: Aggregation and individual differences (ccs_l06_aggregation.md)
7. 12 October: Model comparison 1 (ccs_l07_comparison.md)
8. 14 October: Model comparison 2 (ccs_l08_comparison2.md)
9. 19 October: Case study: Concepts (ccs_l09_concepts.md)
10. 22 October: Causality 1 10.0 Causal vs associative relationships 10.1 Theories of causality 10.2 Models of causal inference in psychology: RW, deltaP, power, Bayes
11. 26 October: Causality 2 11.0 Causal graphical models 11.2 Causal support 11.3 Order effects and process models
12. 29 October: Guest lecture: Tadeg Quillien on Actual causation
13. 02 November: Active learning 1 13.0 Information gain – Gureckis (segue from interventions)
14. 05 November: Active learning 2: RL/Kelsey/Jess/Neil (?)
15. 09 November: overhyps/dirmult
16. 12 November: Guest lecture: Frank Mollica on strong generalization
17. 16 November: Guest lecture: Chentian Jiang on Active causal learning (confirmed)
18. 19 November: automating science
19. 23 November: Guest lecture: Simon on MINEBED (confirmed)
20. 26 November: Guest lecture: Janie (fallback to best practices / recap (ccs_l10_psychology.md))