  We present a new approach for identifying neutrino flares. Using the
unsupervised machine learning algorithm expectation maximization, we reduce
computing times compared to conventional approaches by a factor of $10^5$ on a
single CPU. Expectation maximization is also easily expandable to multiple
flares. We explain the application of the algorithm and fit the neutrino flare
of TXS 0506+056 as an example.

Instrumentation and Methods for Astrophysics;High Energy Astrophysical Phenomena;Computational Physics;Data Analysis, Statistics and Probability