149 citations · 545 across the 20 of their papers we have counts for
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Neural networks trained with SGD learn distributions of increasing complexity
Maria Refinetti, Alessandro Ingrosso, Sebastian Goldt
The ability of deep neural networks to generalise well even when they interpolate their training data has been explained using various "simplicity biases". These theories postulate…
Data-driven emergence of convolutional structure in neural networks
Alessandro Ingrosso, Sebastian Goldt
Exploiting data invariances is crucial for efficient learning in both artificial and biological neural circuits. Understanding how neural networks can discover appropriate represen…
Input correlations impede suppression of chaos and learning in balanced rate networks
Rainer Engelken, Alessandro Ingrosso, Ramin Khajeh +2
Neural circuits exhibit complex activity patterns, both spontaneously and evoked by external stimuli. Information encoding and learning in neural circuits depend on how well time-v…