-
14:00
Data-centric AI
-
Romain Egele
(Université Paris Saclay / Argonne National Laboratory)
-
14:30
Application of Self-organizing maps in high energy physics
-
Kai Habermann
(University of Bonn)
-
14:45
Super-resolution for calorimetry
-
Francesco Di Bello
(INFN and U. of Rome)
-
15:00
Inducing selective posterior-collapse in variational autoencoders by modelling the latent space as a mixture of normal-gamma distributions
-
Emma JOUFFROY
(CEA & IMS)
-
15:15
Deep Multi-task Mining Calabi-Yau Manifolds
-
Riccardo Finotello
(CEA LIST, CEA ISAS)
-
16:00
Scientific inference with imperfect theories: examples with machine learning and neurosciences
-
Gael Varoquaux
(INRIA)
-
16:30
Study of model construction and the learning for hierarchical models
-
Masahiko Saito
(International Center for Elementary Particle Physics, University of Tokyo)
-
16:45
Uncertainty Aware Learning for High Energy Physics With A Cautionary Tale
-
Aishik Ghosh
(UC Irvine)
-
17:00
Graph Neural Networks for track reconstruction at HL-LHC
-
Alexis VALLIER
(Laboratoire des 2 Infinis - Toulouse, CNRS / Univ. Paul Sabatier (FR))
-
17:15
Particle Tracking with Graph Neural Networks
-
Gage DeZoort
(Princeton University)
-
17:30
Jet Energy Corrections with GNN Regression
-
Daniel Holmberg
(CERN)