Solving Fundamental Scientific Problems How can interdisciplinary collaboration accelerate progress in the field of neural networks

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 ... Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... Neural networks, decision trees, simulation and ... The machine learning approach and the Information Virtue – Information Token – Informational. 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 ... in the upper network level. Moreover, in a slightly different direction, research on multi-task learning neural networks, an approach aiming at internal ... Graph neural networks (GNNs) have achieved state-of-the- art performance in graph representation learning by exploit- ing statistical correlations. However, ... ... information transmission by single neurons but not by the entire network. Most surprisingly, addition of a delay can change the dependence of the information ... 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 ... May 9, 2023 ... The article examines the role of the spontaneous activity of neurons, and therefore, of brain neural networks, in information processing. May 1, 2020 ... This review presents a survey on deep learning for multimodal data fusion to provide readers, regardless of their original community, with the fundamentals.