Multi-fidelity ABC

[yannikschaelte]

Feature description
Implement the ability to use low-fidelity models with separate acceptance criterion, to determine whether to simulate the costly high-fidelity model via early rejection/acceptance, and thus overall reduce the required number of high-fidelity model simulations.

E.g. based on:

• Multifidelity Approximate Bayesian Computation
• Multifidelity Approximate Bayesian Computation with Sequential Monte Carlo
  Parameter Sampling

Requires:

• Definition of low-fidelity simulators
• Separate acceptance threshold schemes and distance functions. Can adaptive schemes be used, if e.g. not all particles have high-fidelity simulations?
• Storage extension
• Potentially low-fidelity templates for common models, such as discretization, tau leaping, ML approaches (require separate training)

Motivation/Application
Reduce overall required number of costly high-fidelity simulations by determining early whether a parameter is promising.