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Challenges for Unsupervised Anomaly Detection in Particle Physics
We then show that optimal transport distances to representative events in the background dataset can be used directly for anomaly detection, with performance comparable to the autoencoders.
Jet Charge and Machine Learning
Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider.
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