Capacity-resolution trade-off in the optimal learning of multiple low-dimensional manifolds by attractor neural networks

Aldo Battista, Rémi Monasson

Recurrent neural networks (RNN) are powerful tools to explain how attractors may emerge from noisy, high-dimensional dynamics. We study here how to learn the ~N^(2) pairwise intera…