Bayesian Inference in High-Energy Physics

Contribution List

20. Durham Locals Session: Intro to Bayesian Inference (for our local PhD / PostDoc / Staff)

25/05/2022, 10:00

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.

21. Workshop Official Start & Welcome

25/05/2022, 13:55

2. Mapping Machine-Learned Physics into a Human-Readable Space

Taylor Faucett (UC, Irvine)

25/05/2022, 14:00

Results talks

3. Bayesian Inference of QCD splittings with Invertible Networks

Theo Heimel (U. Heidelberg, ITP)

25/05/2022, 14:35

Results talks

4. 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)

25/05/2022, 15:10

Results talks

6. A graphical multi-fidelity Gaussian process model, with application to emulation of expensive computer simulations

Steffen Bass (Duke University)

25/05/2022, 16:15

Results talks

7. Exploring phase space with Nested Sampling

David Yallup (University of Cambridge)

25/05/2022, 16:50

Results talks

8. Fully Bayesian parameter inference for Markov processes

Darren Wilkinson (Department of Mathematical Sciences at Durham University)

26/05/2022, 09:00

Computer Science and Statistics

9. Bayes linear strategies for emulation and history matching for complex computer models

Michael Goldstein (Department of Mathematical Sciences at Durham University)

26/05/2022, 09:40

Computer Science and Statistics

12. Multilevel Emulation of Complex Computer Models, with application to EAGLE, a Galaxy Formation Simulation

Ian Vernon (Department of Mathematical Sciences at Durham University)

26/05/2022, 10:20

Computer Science and Statistics

10. Enforcing stationarity through the prior in vector autoregressions

Sarah Heaps (Department of Mathematical Sciences at Durham University)

26/05/2022, 11:20

Computer Science and Statistics

11. Contemporaneous MCMC

Louis Aslett (Department of Mathematical Sciences at Durham University)

26/05/2022, 12:00

Computer Science and Statistics

13. Differentiable programming and its applications

Lukas Heinrich (Technical University Munich)

26/05/2022, 14:40

Topics talks on Bayesian Inference in HEP

14. HEP Simulator issues tackled with Bayesian Inference

Manuel Szewc (IJS & ICAS-UNSAM)

26/05/2022, 15:20

Topics talks on Bayesian Inference in HEP

15. Quantifying Uncertainty in Deep Learning

Mike Walmsley (University of Manchester)

26/05/2022, 16:30

Topics talks on Bayesian Inference in HEP

16. The inverse problem challenge in lattice QCD

Alexander Rothkopf (University of Stavanger)

26/05/2022, 17:10

Topics talks on Bayesian Inference in HEP

17. Causal Inference

Ezequiel Alvarez (ICAS, UNSAM)

27/05/2022, 09:00

Topics talks on Bayesian Inference in HEP

18. Representation Learning for HEP

Barry Dillon (University of Heidelberg)

27/05/2022, 09:40

Topics talks on Bayesian Inference in HEP

19. Bayesian community criteria for anomaly evaluation

Jernej Kamenik (Jozef Stefan Institute & Ljubljana University)

27/05/2022, 10:20

Topics talks on Bayesian Inference in HEP