Machine learning allows us to detect millions of tiny earthquakes, but our current tools struggle to process this “data tsunami” with high precision. While a popularized mathematical approach called “Bayesian inference” can tell us exactly how reliable an earthquake’s location is, it is usually too slow to handle such massive amounts of information. This is especially true for “double-difference”…
