Choose your adventure

At this stage we will be training a neural network to approximate a likelihood or a likelihood ratio for down-stream statistical analysis. The papers mentioned in the Introduction describe these techniques in detail. There are basically three options for this step:

• An approximate likelihood ratio (recommended for the tutorial, ~20 min).

• An approximate score, which is like the optimal observables (stretch goal for the tutorial).

• An approximate likelihood (like a high-dimensional histogram, but with a neural network).

This is where the machine learning training happens, and MadMiner uses Pytorch.