Semantic Relationships

Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... Sep 10, 2019 ... Using a genetic algorithm approach to find optimal neural network structures for model-free policy learning in reinforcement learning; Using ... Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts ... Jan 10, 2024 ... (2007, 2010), for instance, used a network composed of two coupled rings, representing sensory and frontal cortical modules, to model the ... Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ... ... information-processing system in order to have a mind. The answer is the ... neural network (see Shea, 2007). Nevertheless, we can ignore this set of ... performing the functions of associative memory. L. Figure 1. Dependence of the main neural network informational charaaeristi~ on the number of stored templates ... View details for Real-time Twitter data sentiment analysis to predict the recession in the UK using Graph Neural Networks. We present a review on the recent advances and emerging opportunities around the theme of analyzing deep neural networks (DNNs) with information-theoretic ... ... Learning Capability of Deep Neural Networks: A Positivist Perspective Jaebong Son and Chang Heon Lee. PDF · The Sky Is the Limit: A Review of Drone Research ...