Name: Bayesian Inference in High-Energy Physics
Start: 2022-05-25T09:00:00+01:00
End: 2022-05-27T18:00:00+01:00
Location: IPPP

Bayesian Inference in High-Energy Physics

from Wednesday 25 May 2022 (09:00) to Friday 27 May 2022 (18:00)

Monday 23 May 2022
Tuesday 24 May 2022
Wednesday 25 May 2022

10:00 Durham Locals Session: Intro to Bayesian Inference (for our local PhD / PostDoc / Staff)
Durham Locals Session: Intro to Bayesian Inference (for our local PhD / PostDoc / Staff)
10:00 - 11:30
Room: OC218 Attendance from workshop participants is welcome but not expected. This session is aimed at introducing some of the basic ideas of Bayesian Inference to our local PhD/ PostDocs and interested staff members.

13:55 Workshop Official Start & Welcome
Workshop Official Start & Welcome
13:55 - 14:00
Room: OC218
14:00
14:00 - 18:00
Room: OC218
Contributions

14:00 Mapping Machine-Learned Physics into a Human-Readable Space - Taylor Faucett (UC, Irvine)

14:35 Bayesian Inference of QCD splittings with Invertible Networks - Theo Heimel (U. Heidelberg, ITP)

15:10 How well do we know the neutron-matter equation of state at the densities inside neutron stars? A Bayesian approach with correlated uncertainties - Jordan Melendez (The Ohio State University)

16:15 A graphical multi-fidelity Gaussian process model, with application to emulation of expensive computer simulations - Steffen Bass (Duke University)

16:50 Exploring phase space with Nested Sampling - David Yallup (University of Cambridge)
Thursday 26 May 2022
09:00 Mathematical aspects of Bayesian inference, by the Statistics group @ Durham
Mathematical aspects of Bayesian inference, by the Statistics group @ Durham
09:00 - 12:50
Room: OC218
Contributions

09:00 Fully Bayesian parameter inference for Markov processes - Darren Wilkinson (Department of Mathematical Sciences at Durham University)

09:40 Bayes linear strategies for emulation and history matching for complex computer models - Michael Goldstein (Department of Mathematical Sciences at Durham University)

10:20 Multilevel Emulation of Complex Computer Models, with application to EAGLE, a Galaxy Formation Simulation - Ian Vernon (Department of Mathematical Sciences at Durham University)

11:20 Enforcing stationarity through the prior in vector autoregressions - Sarah Heaps (Department of Mathematical Sciences at Durham University)

12:00 Contemporaneous MCMC - Louis Aslett (Department of Mathematical Sciences at Durham University)
13:00 Buffet Lunch
Buffet Lunch
13:00 - 14:30
Room: OC218
14:40 Topics talks on Bayesian Inference in HEP
Topics talks on Bayesian Inference in HEP
14:40 - 18:40
Room: OC218
Contributions

14:40 Differentiable programming and its applications - Lukas Heinrich (Technical University Munich)

15:20 HEP Simulator issues tackled with Bayesian Inference - Manuel Szewc (IJS & ICAS-UNSAM)

16:30 Quantifying Uncertainty in Deep Learning - Mike Walmsley (University of Manchester)

17:10 The inverse problem challenge in lattice QCD - Alexander Rothkopf (University of Stavanger)
19:00 Conference Dinner
Conference Dinner
19:00 - 21:00
Friday 27 May 2022
09:00 Topics talks on Bayesian Inference in HEP
Topics talks on Bayesian Inference in HEP
09:00 - 11:00
Room: OC218
Contributions

09:00 Causal Inference - Ezequiel Alvarez (ICAS, UNSAM)

09:40 Representation Learning for HEP - Barry Dillon (University of Heidelberg)

10:20 Bayesian community criteria for anomaly evaluation - Jernej Kamenik (Jozef Stefan Institute & Ljubljana University)
11:00 Coffee
Coffee
11:00 - 11:30
Room: OC218

11:30

11:30 - 12:30
Room: OC218

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