A Wasserstein-distance-trained normalized autoencoder detects semivisible jets in simulated LHC events with AUCs around 0.69–0.77, outperforming standard and normalized autoencoders on a ttbar background.
Parallel Distributed Processing, Volume 1: Explorations in the Microstructure of Cognition: Foundations
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Wasserstein normalized autoencoder for anomaly detection
A Wasserstein-distance-trained normalized autoencoder detects semivisible jets in simulated LHC events with AUCs around 0.69–0.77, outperforming standard and normalized autoencoders on a ttbar background.