Limited Data

Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... ... neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition. Klinkner, K.L., Shalizi, C.R., Camperi, M.F. Measuring shared information and coordinated activity in neuronal networks (2005). Advances in Neural Information ... Essentially, the network learns how to learn, and that is a really puzzling result. 30th Conference on Neural Information Processing Systems (NIPS 2016), ... Jan 9, 2024 ... 43. Francis, N.A. ... Sequential transmission of task-relevant information in cortical neuronal networks. Cell Rep. 2022; 39, 110878. Dec 20, 2024 ... In ecosystems, financial markets, and neural networks, entropy fluctuates as new information reshapes the probability landscape. 4.2 The ... Jun 23, 2020 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure. 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 ... The human brain is often used as an analogy to explain neural networks, however this is not particularly helpful as it implies machines understand information ... Dec 19, 2019 ... Abstract: Attribution methods provide insights into the decision-making of machine learning models like artificial neural networks.