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Aug 9, 2024 ... Neural networks are modeled after the human brain's structure and function. A neural network consists of interconnected layers of nodes ( ... Klinkner, K.L., Shalizi, C.R., Camperi, M.F. Measuring shared information and coordinated activity in neuronal networks (2005). Advances in Neural Information ... Informational capacity and recall quality in sparsely encoded Hopfield-like neural network: analytical approaches and computer simulation Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ... We then perform information le- sions of individual neurons to determine their contribution to each task. Following that, we investigate the ability of two. Sep 5, 2024 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure in ... May 1, 2020 ... This review presents a survey on deep learning for multimodal data fusion to provide readers, regardless of their original community, with the fundamentals. ... information is transformed into valuable information with neural net. The individual element of the neural network, i.e., the living neuronal cell, is ... Dec 19, 2019 ... Abstract: Attribution methods provide insights into the decision-making of machine learning models like artificial neural networks. Nov 2, 2004 ... ... neural system. ... Dehaene S, Sergent C, Changeux JP: A neuronal network model linking subjective reports and objective physiological data during ...