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Found 3 papers, 2 papers with code
Unsupervised Learning for Identifying Events in Active Target Experiments
We also explore the application of clustering the latent space of autoencoder neural networks for event separation.
Machine Learning Methods for Track Classification in the AT-TPC
We evaluate machine learning methods for event classification in the Active-Target Time Projection Chamber detector at the National Superconducting Cyclotron Laboratory (NSCL) at Michigan State University.
Automatic trajectory recognition in Active Target Time Projection Chambers data by means of hierarchical clustering
In this article, we propose a non-parametric algorithm that is based on the idea of clustering point triplets instead of the original points.
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