Genome Analysis

The informational aspects of neural networks performing associative memory following Hebbian learning are analysed in detail. The recall process is decomposed ... Neural networks, decision trees, simulation and ... The machine learning approach and the Information Virtue – Information Token – Informational. Mar 24, 2024 ... Graph neural networks (GNNs) have achieved state-of-the-art results on many graph representation learning tasks by exploiting statistical ... We propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma ... Jan 9, 2024 ... 43. Francis, N.A. ... Sequential transmission of task-relevant information in cortical neuronal networks. Cell Rep. 2022; 39, 110878. Sep 4, 2020 ... TABOO: De- tecting unstructured sensitive information using recursive neural networks. In Proceedings of the 33rd International Conference on. ... information is transformed into valuable information with neural net. The individual element of the neural network, i.e., the living neuronal cell, is ... Information integration is a measure, developed by Tononi and co-researchers, of the capacity for dynamic neural networks to be in informational states ... Graph neural networks (GNNs) have achieved state-of-the- art performance in graph representation learning by exploit- ing statistical correlations. However, ... ... information theory in the evaluation of single neuron responses and neural networks. The question of the neural code has been debated heatedly since the ...