Les Houches

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ML: Generative model projects

Discussed the topics we like to study:

• Interpolation and extrapolation properties of generative models

Aims: Define toys cases where the density d(x) is known, Sample training data from this.

    Then train generative model on training data. Forecast d(x) with that model.
    Derive pull distribution for the integral of the density in some phase space regions to
    check how much and if this scales better than sqrt(N) where N are the number of training data 
    points in that phase space regions. 
    Also derive uncertainties via envelope of networks (e.g. via MC dropout, 
    https://arxiv.org/abs/1506.02142)
    
* Transfer learning
* Simulator
* Shower development etc.