The fast committor machine: Interpretable prediction with kernels

Understand

In the study of stochastic systems, the committor function describes the probability that a system starting from an initial configuration $x$ will reach a set $B$ before a set $A$.

• This paper introduces an efficient and interpretable algorithm for approximating the committor, called the "fast committor machine" (FCM).
• The FCM uses simulated trajectory data to build a kernel-based model of the committor.
• The kernel function is constructed to emphasize low-dimensional subspaces that optimally describe the $A$ to $B$ transitions.