Agents

a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process. Klinkner, K.L., Shalizi, C.R., Camperi, M.F. Measuring shared information and coordinated activity in neuronal networks (2005). Advances in Neural Information ... Nov 9, 2018 ... You don't lose a few neural connections and with it 80% of your consciousness. The richness of our stream of experience is stable across small ... Feb 7, 2018 ... ... information than excitatory connections, known to enhance entropy in the network. ... Neural information · Neuronal dynamics · Topological tools ... Apr 28, 2021 ... First, the Information Bottleneck Principle is not the same as bottleneck layers in networks like auto-encoders. These can serve as information ... Jan 9, 2024 ... 43. Francis, N.A. ... Sequential transmission of task-relevant information in cortical neuronal networks. Cell Rep. 2022; 39, 110878. We present a review on the recent advances and emerging opportunities around the theme of analyzing deep neural networks (DNNs) with information-theoretic ... information carried by the network via neural codes. 1.3. Consciousness and Informational Complexity. The idea of computational mod- els of consciousness ... ... neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition. ... system can become highly synergistic; and (b) how informational states map onto artificial neural networks in various learning modes. Here we employ an ...