These models typically make a concrete prediction based on an input. Mit researchers designed a computationally efficient algorithm for machine learning with symmetric data that also requires fewer data for training than conventional approaches. This group serves as a forum for notices and announcements of interest to the machine learning community.
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New prediction model could improve the reliability of fusion power.
The model could have applications in.
The approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.