Models, Data & AI Workgroup- 19/10/2021 -18:00 CET - 5p.m. UK Time.

Agenda:

• Welcome
• Discussion with Kevin Korfmann (TUM)

Abstract: We aim to give a conceptual overview of an alternative way of doing parameter inference with deep learning, which integrates real data during the inference process rather than training only on simulated data alone, along the line of the paper by Wang et al [1] . We will not be focusing on the results so much, but rather on the methods with a brief overview slides one on machine learning in general and on population genetics.

[1] Wang et al., Automatic inference of demographic parameters using generative adversarial networks.
Mol Ecol Resour. 2021 Mar 20.doi: 10.1111/1755-0998.13386.
https://pubmed.ncbi.nlm.nih.gov/33745225/

Background: This is a workgroup meeting in the areas of mathematical modelling, data analysis, machine learning and artificial intelligence. Current activities:

• Parametrisation of epidemiological models, in cooperation with the Covid-19 project.
• Joint publications starting with epidemiological models based on rule-based systems (reaction kinetics)
• Implementations are done with RStudio and Jupyter Notebook/Lab, at least initially.

ZOOM Meeting: The meeting is Tuesdays at 18:00 CET (Paris-Berlin-Rome), 5:00 p.m. GMT (London). The Zoom URL is

https://us02web.zoom.us/j/81572993899?pwd=UGFNaWtUTWNLUHZLb1ZEV29LWDJkdz09

Meeting-ID: 815 7299 3899
Code: 364883

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