Learning Sequence Attractors in Recurrent Networks with Hidden Neurons

arXiv:2404.02729v1 Announce Type: cross
Abstract: The brain is targeted for processing temporal sequence information. It remains largely unclear how the brain learns to store and retrieve sequence memories. Here, we study how recurrent networks of binary neurons learn sequence attractors to store predefined pattern sequences and retrieve them robustly. We show that to store arbitrary pattern sequences, it is necessary for the network to include hidden neurons even though their role in displaying sequence memories is indirect. We develop a …

abstract arxiv binary brain cs.ai cs.lg cs.ne hidden information learn memories networks neurons processing show store study temporal them type