Oct 19 – 23, 2020
Europe/Zurich timezone

Contribution List

69 / 69
Andrea Wulzer (CERN and EPFL), David Rousseau (LAL-Orsay, FR), Gian Michele Innocenti (CERN), Lorenzo Moneta (CERN), Dr Pietro Vischia (Universite Catholique de Louvain (UCL) (BE)), Riccardo Torre (CERN), Simon Akar (University of Cincinnati (US))
10/20/20, 10:00 AM
Han Hubert Dols (CERN), Nick Ziogas (CERN)
10/20/20, 10:15 AM
Daniel Thomas Murnane (Lawrence Berkeley National Lab. (US)), Xiangyang Ju (Lawrence Berkeley National Lab. (US))
10/22/20, 5:00 PM
Jessica N. Howard (Department of Physics & Astronomy, UC Irvine), Jessica Nicole Howard (University of California Irvine (US))
10/23/20, 10:00 AM
3 ML for simulation and surrogate model : Application of Machine Learning to simulation or other cases where it is deemed to replace an existing complex model
Regular talk

We introduce a novel strategy for machine-learning-based predictive simulators, which can be trained in an unsupervised manner using observed data samples to learn a predictive model of the detector response and other difficult-to-model transformations. Particle physics detectors cannot directly probe fundamental particle collisions. Instead, statistical inference must be used to surmise...