Based on the established task of identifying boosted, hadronically decaying
top quarks, we compare a wide range of modern machine learning approaches.
Unlike most established methods they rely on low-level input, for instance
calorimeter output. While their network architectures are vastly different,
their performance is comparatively similar. In general, we find that these new
approaches are extremely powerful and great fun.Comment: Yet another tagger included