4th Inter-experiment Machine Learning Workshop

Scientific Programme

1 ML for data reduction : Application of Machine Learning to data reduction, reconstruction, building/tagging of intermediate object

2 ML for analysis : Application of Machine Learning to analysis, event classification and fundamental parameters inference

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

4 Fast ML : Application of Machine Learning to DAQ/Trigger/Real Time Analysis

5 ML algorithms : Machine Learning development across applications

6 ML infrastructure : Hardware and software for Machine Learning

7 ML training, courses and tutorials

8 ML open datasets and challenges

9 ML for astroparticle

10 ML for experimental particle physics

11 ML for phenomenology and theory

12 ML for particle accelerators

13 Other