Maximizing Redundancy as a Principle for Learning Associative Memory in Hopfield Networks
Blümel M; Schneider AC; Neuhaus V; Ehrlich DA; Graetz M; Wibral M; Makkeh A; Priesemann V
Researchers studied how brain-like memory networks can store and recall patterns from incomplete clues. They found that making the network focus on shared information between inputs greatly improved its memory, helping it remember much more than older versions.