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1 ML for object identification and reconstruction
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2 ML for analysis : event classification, statistical analysis and inference, including anomaly detectio
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3 ML for simulation and surrogate model : Application of Machine Learning to simulation or other cases where it is deemed to replace an existing complex model
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4 Fast ML : Application of Machine Learning to DAQ/Trigger/Real Time Analysis
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5 ML infrastructure : Hardware and software for Machine Learning
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6 ML training, courses, tutorial, open datasets and challenges
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7 ML for phenomenology and theory (only if does not fit in Tracks above)
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8 ML for particle accelerators (only if does not fit in Tracks above)
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9 Other
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