3 papers
cs.LG2025
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine C. J. Dominé, Nicolas Anguita, Alexandra M. Proca +4
Biological and artificial neural networks develop internal representations that enable them to perform complex tasks. In artificial networks, the effectiveness of these models reli…
cs.LG2025
Flexible task abstractions emerge in linear networks with fast and bounded units
Kai Sandbrink, Jan P. Bauer, Alexandra M. Proca +3
Animals survive in dynamic environments changing at arbitrary timescales, but such data distribution shifts are a challenge to neural networks. To adapt to change, neural systems m…
cs.LG2024
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning
Daniel Kunin, Allan Raventós, Clémentine Dominé +4
While the impressive performance of modern neural networks is often attributed to their capacity to efficiently extract task-relevant features from data, the mechanisms underlying…