Working Group 1

WG1 · Machine Learning Applications for Collider Physics

WG1 transforms cutting-edge machine learning research into deployable models entering into the experimental workflow for triggering, reconstruction and analysis while delivering robust and improved performance.

Co-Leaders: Dr Jackson Barr, Prof Pietro Vischia

• Advanced ML architectures for detector reconstruction and precision triggering.
• Unsupervised and weakly supervised anomaly detection to uncover unexpected signals.
• Physics-informed networks with quantified uncertainties for high-stakes analyses.