Understanding Language Structure

Nov 2, 2004 ... ... neural system. ... Dehaene S, Sergent C, Changeux JP: A neuronal network model linking subjective reports and objective physiological data during ... Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ... ... informational differences among them, efficiently coordinating and integrating the sub-prediction results. Secondly, a two-stage predictive model selection ... ... information is transformed into valuable information with neural net. The individual element of the neural network, i.e., the living neuronal cell, is ... Dec 31, 2022 ... We relax these limitations using deep learning methods. We use a neural network to classify insurees into joint choice of coverage and claim ... ... information transmission by single neurons but not by the entire network. Most surprisingly, addition of a delay can change the dependence of the information ... Jan 16, 2021 ... ... informational and non-informational classes, respectively ... The deep neural network (DNN) classifier obtained the highest accuracy (95.2%). Sep 5, 2024 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure in ... Klinkner, K.L., Shalizi, C.R., Camperi, M.F. Measuring shared information and coordinated activity in neuronal networks (2005). Advances in Neural Information ... Mar 4, 2016 ... For the multiplex neural networks, we find that intra and inter couplings will complementarily cooperate to complex behaviour if the two neural ...