Name: Uncertainty Quantification (UQ) at the Extremes (ISNET-6)
Start: 2018-10-08T18:00:00+02:00
End: 2018-10-12T18:00:00+02:00
Location: TU Darmstadt

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Contributions*

A new bootstrap-based fitting method

A statistical study of the transition from isolated resonances to the continuum

An introduction to Bayesian methods for physicists

Approximate Bayesian computation for expensive simulators

Bayesian Model Mixing: A Nuclear Physics Perspective

Bayesian optimization of the NN interaction

Bayesian parameter estimation and model evidence for nuclear EFT

Bayesian parameter estimation in NN scattering

Capturing uncertainty about model inputs using expert elicitation

Compton scattering observables, errors, and goals

Computer model calibration, emulation, and discrepancy analysis

Dynamical modeling of heavy-ion reactions

EMMI

Examining the Origin of the r-process Rare-Earth Abundance Peak with Markov Chain Monte Carlo

Extrapolations with Bayesian machine learning

Gaussian Processes and Expected Improvement for Fitting Nuclear Models

Global fits and Bayesian inference in "Beyond the Standard Model" physics

Global sensitivity analysis for complex models

Machine Learning and Precision Analysis at GlueX

Model selection for the spectrum of light baryons

Model-based extrapolation of nuclear observables via Bayesian machine learning

Nuclear structure corrections in muonic atoms: Quantifying theoretical uncertainties

Nucleon axial form factor from a Bayesian neural-network analysis of neutrino-scattering data

Nucleosynthesis in neutrino-driven supernova ejecta: astrophysical and nuclear physics uncertainties

Observables probing the nuclear pairing functional

Optimization and parameter reduction in nuclear EDFs

Optimization problems in nuclear theory

Quantifying Errors from Chiral Effective Field Theory

Quantifying errors in EFTs of heavy nuclei

Statistical methods for Parton Distribution Functions

Uncertainty estimates for nuclear matter and neutron-rich nuclei

Uncertainty estimates from R-matrix analyses

Uncertainty in nuclear-reaction calculations involving halo nuclei

Uncertainty quantification for the three-nucleon force with light-ion reactions

Using Bayesian approaches to design new expensive experiments

Using Model Emulators for An Inverse Problem

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08/10/2018

09/10/2018

10/10/2018

11/10/2018

12/10/2018

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Uncertainty Quantification (UQ) at the Extremes (ISNET-6)

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