Fonctionne avec Indico
v3.2.8
Motivated by the large volume and high complexity of experimental data and mathematical structures, particle physics has a long tradition of employing state of the art computing and analysis techniques. Recent progress in machine learning and artificial intelligence have further pushed this trend, and these approaches are now ubiquitous in our field. This talk will introduce generative machine learning models, and explore how these tools can be used to both speed-up the simulation of particle showers in complex detectors, and to discover signals of physics beyond the standard model in a largely model independent way.
Coffee/tea/viennoiseries will be served from 10 am.