Biologically Inspired

Informational capacity and recall quality in sparsely encoded Hopfield-like neural network: analytical approaches and computer simulation In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... Neural networks, decision trees, simulation and ... The machine learning approach and the Information Virtue – Information Token – Informational. Feb 25, 2025 ... Neurons are responsible for sending and receiving neurotransmitters—chemicals that carry information between brain cells. Depending on its ... Nov 2, 2004 ... ... neural system. ... Dehaene S, Sergent C, Changeux JP: A neuronal network model linking subjective reports and objective physiological data during ... Sep 4, 2020 ... TABOO: De- tecting unstructured sensitive information using recursive neural networks. In Proceedings of the 33rd International Conference on. We do so by performing experiments on artificial neural networks in the context of fairness in machine learning, where the goal is to induce fairness in the ... Sep 4, 2023 ... ... neuronal networks or whether it is related to informational load. ... To explore this topic, we used an in vitro neural network of cortical ... Feb 24, 2020 ... We show how to encode both types of domain knowledge into the widely used Gaussian scale mixture priors with Automatic Relevance Determination. View details for Real-time Twitter data sentiment analysis to predict the recession in the UK using Graph Neural Networks.