Standards for sharing models:

• LWTNN
• ONNX

Analyses that have provided ML models:

• ATLAS-SUSY-2019-04
• ATLAS-SUSY-2018-30
• ?

Discussion during the Dec '22 reinterpretation workshop: link.

Overleaf document for writeup

Propose to build a surrogate model using the JetClass dataset [1], trying to approximate the output of a state-of-the-art attention based tagger (ParT, [1]) – which uses low-level inputs including vertex information – with a network only using high-level kinematics / n-subjettiness. Hamburg is preparing a simplified dataset (dropping low level features, adding ParT output, restricting to hadronic top vs light quark/gluon;  reducing examples/class to  2M train / class; 500k test/class; 1M  val/class)

Based on this we can test different surrogate models, Bayesian NN, explicit sampling.

[1] Paper that introduced jetClass data: arXiv:2202.03772