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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 ... performing the functions of associative memory. L. Figure 1. Dependence of the main neural network informational charaaeristi~ on the number of stored templates ... in the upper network level. Moreover, in a slightly different direction, research on multi-task learning neural networks, an approach aiming at internal ... ... neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition. ... informational methods. The role of informational methods is to model ... Mechanical modeling; neural network; column-base connection; composed modeling ... Just as the brain has interconnected neurons, a neural network has tiny interconnected nodes that work together to process information. Neural networks improve ... classification via convolutional deep neural network. In Proceedings of COLING. 2014, the 25th International Conference on Computational Linguistics ... In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... ... system can become highly synergistic; and (b) how informational states map onto artificial neural networks in various learning modes. Here we employ an ...