Concepts

The ZüNIS library provides three level of abstractions, to allow both high-level and fine-grained control:

1. Integrators are the highest level of abstraction and control function integration strategies. They can automate trainer and flow creation.

2. Trainers are one level below and steer model training through loss functions, optimizers, sampling etc. They can automate flow creation.

3. Normalizing Flows are neural-network-based bijections from the unit hypercube to itself. They are the actual trainable sampling mechanism that we use to sample points for Monte Carlo integration.

An Integrator contains a Trainer, which contains a Flow. Each level of abstraction can either be instantiated by providing it it with an explicit object of the lower level, or using an API which builds the lower-level constructs automatically.

../_images/Abstractions.png