Implementation of Variational Autoencoder on the simulated particle collider data

Abstract: We study the possibility of applying deep learning algorithms, suchas Variational Autoencoders, on simulated particle collider data to detectBeyond the Standard Model events. In this report, we apply three dif-ferent processes of training the data for better eciency and the resultsof said training on detecting anomalies. Links to the training and testingdata can be found here: https://www.phenomldata.org/