PHYSTAT-Systematics 2021, 1-3 Nov + 10 Nov

Contribution List

1. Welcome to workshop

11/1/21, 2:00 PM

Session 1a

2. Setting the Scene

Louis Lyons (Imperial College (GB))

11/1/21, 2:05 PM

Session 1a

3. Statistician's overview of Systematics

David van Dyk (University of California, Irvine), David van Dyk

11/1/21, 2:30 PM

Session 1a

4. Systematics of direct Dark Matter signals experiments and models

Knut Morå (Columbia University), Knut Morå (Stockholm University)

11/1/21, 3:10 PM

Session 1a

22. Response 1

Alessandra Brazzale (Padova)

11/1/21, 3:50 PM

Session 1a

5. Systematics at LHC for event selection, discovery and limits

Lukas Alexander Heinrich (CERN)

11/1/21, 4:20 PM

Session 1b

6. Precision measurements

Alexander Glazov (Deutsches Elektronen-Synchrotron (DE))

11/1/21, 5:00 PM

Session 1b

7. Response 2

Tom Junk (Department of Physics), Tom Junk (Fermi National Accelerator Lab. (US))

11/1/21, 5:40 PM

Session 1b

23. A call to action: Honoring PHYSTAT's 20 year old agreement

Kyle Cranmer (NYU), Kyle Stuart Cranmer (New York University (US))

11/1/21, 6:00 PM

Session 1b

8. Systematics in a selection of neutrino oscillation experiments

Christophe Bronner (Kamioka, ICRR, University of Tokyo)

11/2/21, 2:00 PM

Session 2a

9. Flavour physics

Thomas Blake (University of Warwick)

11/2/21, 2:40 PM

Session 2a

10. Response 3

Chad Schafer (CMU)

11/2/21, 3:20 PM

Session 2a

11. Theory uncertainties

Frank Tackmann, Frank Tackmann (Deutsches Elektronen-Synchrotron (DE))

11/2/21, 4:00 PM

Session 2b

12. Data mismodelling

Adinda De Wit (Universitaet Zuerich (CH))

11/2/21, 4:40 PM

Session 2b

14. Response 4

Larry Wasserman (CMU)

11/2/21, 5:20 PM

Session 2b

13. How the Bootstrap eliminates nuisance parameters for confidence intervals

Brad Efron (Stanford)

11/2/21, 5:40 PM

Session 2b

15. Systematic uncertainties in unfolding particle spectra

Mikael Kuusela (Carnegie Mellon University (US))

11/3/21, 2:00 PM

Session 3a

16. Three approaches to Systematics with Machine Learning

Kyle Stuart Cranmer (New York University (US))

11/3/21, 2:40 PM

Session 3a

17. Response 5

Anthony Davison (EPFL)

11/3/21, 3:20 PM

Session 3a

24. Transfer Learning for data-driven background modelling: Optimal Transport v Classifier Extrapolation

Tudor Manole (CMU)

11/3/21, 4:00 PM

Session 3b

25. Systematic effects versus nuisance parameters

Richard Lockhart (SFU)

11/3/21, 4:25 PM

Session 3b

26. Universal Inference

Larry Wasserman (Carnegie Mellon University)

11/3/21, 4:50 PM

Session 3b

27. Bayesian reflection on Systematics

James Berger (Duke University)

11/3/21, 5:15 PM

Session 3b

28. Partially Bayes : An inter-perspective approach for handling nuisance parameters

Xiao-Li Meng (Harvard)

11/3/21, 5:40 PM

Session 3b

Recorded talk, available for viewing afterwards
Send comments/questions for Prof. Meng to l.lyons@physics.ox.ac.uk

19. Final remarks ** N.B. Summary Talks on Nov 10th **

Olaf Behnke (Deutsches Elektronen-Synchrotron (DE))

11/3/21, 5:42 PM

Session 3b

20. Physicist's summary

Nicholas Wardle (Imperial College (GB))

11/10/21, 3:00 PM

Summary presentations

21. Statistician's summary

Sara Algeri (University of Minnesota)

11/10/21, 3:45 PM

Summary presentations

18. Short talks by Statisticians

Session 3b