theory part where we mention the most commonly used methods, i.e. bin-by-bin, pure matrix inversion, least-square minimisation with or without Tikhonov regularisation, D'Agostini iterative unfolding, maximum likelihood with combine, ...
to recycle the examples in TUnfold for the exercises
additional examples with combine
11:50
→
11:55
Topical exercise: ML (PyTorch)5m
12:00
→
12:05
Topical exercise: CMSSW5m
Speakers:
Océane Poncet, Suvankar Chowdhury, Suvankar Roy Chowdhury
slides shown will send them, focus on MiniAOD (not Nano), runTheMatrix to understand a full chain, introductory slides maybe also a bit about releases, parameters, configdump