The FAIR Universe -- HiggsML Uncertainty Challenge focuses on measuring the physics properties of elementary particles with imperfect simulators.
The goal of the challenge is to bring together the physics and machine learning communities to advance our understanding and methodologies in handling systematic (epistemic) uncertainties within AI techniques.
The challenge has run 1st October 2024 till 15th March 2025, and the dataset and benchmark will remain available to evaluate further developments.
It has been an official NeurIPS 2024 competition.
This event is the closing workshop where the best participant contributions will be presented, as well as keynotes addressing the overall topic of uncertainty-aware training.
It is run as a satellite workshop for the 7th CERN Interexperiment Machine Learning workshop. We recommend participants to Fair Universe workshop to register here and also for the main free IML workshop, in particular for anything concerning CERN access and accommodation
Useful links:
- Fair Universe web site
- Fair Universe HiggsML uncertainties competition site
- NeurIPS 2024 Fair universe workshop
- Fair universe whitepaper
This is a collaboration between LBNL Berkeley, University of Washington, Chalearn and University Paris-Saclay. See the whitepaper for the complete author list.