The fast committor machine: Interpretable prediction with kernels.

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.

Exploring thematic structure and predicted functionality of 16S rRNA amplicon data.

Analysis of microbiome data involves identifying co-occurring groups of taxa associated with sample features of interest (e.g., disease state).

Transient probability currents provide upper and lower bounds on non-equilibrium steady-state currents in the Smoluchowski picture.

Probability currents are fundamental in characterizing the kinetics of nonequilibrium processes. Notably, the steady-state current J for a source-sink system can provide the exact mean-first-passage time (MFPT) for the transition from the source to sink. Because transient nonequilibrium behavior is quantified in some modern path sampling approaches, such as the "weighted ensemble" strategy, there is strong motivation to determine bounds on J-and hence on the MFPT-as the system evolves in time.