Storing and Processing Sequential Information What are external memory mechanisms for neural networks

ABSTRACT. Introduction: Natural Language Processing through artificial neural networks has gaps that can be addressed by Information Science. Neural networks can realize conditional distributions of the form p(y. z I x. u) specified by network parameter u. The set of such realizable distributions is a ... ... neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of ... In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... Apr 8, 2025 ... Neural networks are computational models that learn how to recognize patterns, develop predictions, and process data. By using algorithms, ... Neural networks, decision trees, simulation and ... The machine learning approach and the Information Virtue – Information Token – Informational. We propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma ... Information integration is a measure, developed by Tononi and co-researchers, of the capacity for dynamic neural networks to be in informational states ... Feb 26, 2024 ... This article introduces a quantitative approach to modeling the cost of control in a neural network architecture when it is required to execute one or more ... The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar is a very interdisciplinary work. Anyone interested in the ...