Power Efficiency

Jan 29, 2024 ... We will see how ANN-assisted mixture space exploration can adapt to dynamic mixtures and balance the local and global information. Section 3 ... Jun 29, 2022 ... Neural Networks are one particular type of Machine Learning technique. They are a type of artificial intelligence modeled on the brain. information carried by the network via neural codes. 1.3. Consciousness and Informational Complexity. The idea of computational mod- els of consciousness ... in the upper network level. Moreover, in a slightly different direction, research on multi-task learning neural networks, an approach aiming at internal ... ... information theory in the evaluation of single neuron responses and neural networks. The question of the neural code has been debated heatedly since the ... Essentially, the network learns how to learn, and that is a really puzzling result. 30th Conference on Neural Information Processing Systems (NIPS 2016), ... Sep 22, 2020 ... By recruiting adjacent neurons into oscillations, waves of synchronously firing neuronal networks—and thereby conscious thoughts—can travel ... Jun 23, 2020 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure. ... informational differences among them, efficiently coordinating and integrating the sub-prediction results. Secondly, a two-stage predictive model selection ... Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ...