Neural Dynamics as the Composition of Quantized Units
Deep learning is commonly interpreted at two levels: the macroscopic, through aggregate trends in loss summarized by scaling laws, and the microscopic, through neurons, features, and circuits. A central challenge is understanding how these levels connect, so that we can explain how elementary computations compose and c...
J. Minniti, Aravinth Kulanthaivelu, Richard Sproat
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