Machine learning pipeline for direct detection experiments
After painstakingly thorough work, I am pleased to see our new paper, led by Andre Scaffidi, out today as part of the DARWIN direct dark matter detection collaboration! 👏 We use a semi-supervised anomaly detection pipeline, comprising of a variational autoencoder trained on simulated background events and a classifier distinguishing between electronic and nuclear recoils, […]
