Analyzing Large Datasets

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 ... Aug 30, 2023 ... To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of 'Pong' to ... Klinkner, K.L., Shalizi, C.R., Camperi, M.F. Measuring shared information and coordinated activity in neuronal networks (2005). Advances in Neural Information ... ... information transmission by single neurons but not by the entire network. Most surprisingly, addition of a delay can change the dependence of the information ... same ink serve more than one informational purpose. Using large ... Physics-Informed Neural Networks for Anomaly Detection: A Practitioner's Guide ... We propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma ... Abstract. The concept of Learning by Stimulus Avoidance (LSA) has been proposed in recent literature, and the methods of avoiding stimuli: action, prediction, ... View details for Real-time Twitter data sentiment analysis to predict the recession in the UK using Graph Neural Networks. Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ... The informational aspects of neural networks performing associative memory following Hebbian learning are analysed in detail. The recall process is decomposed ...