Common Sense Reasoning

Jan 9, 2024 ... 43. Francis, N.A. ... Sequential transmission of task-relevant information in cortical neuronal networks. Cell Rep. 2022; 39, 110878. Sep 11, 2020 ... Alternatively, it is. 10. Page 29. 2.1. Preliminaries on convolutional neural networks often found that adding depth to the network by stacking ... Mar 24, 2024 ... Graph neural networks (GNNs) have achieved state-of-the-art results on many graph representation learning tasks by exploiting statistical ... Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ... Sep 27, 2024 ... We exploit large-scale content consumption information from the perspective of heterogeneous networks and learn latent customer representation ... 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. ... informational differences among them, efficiently coordinating and integrating the sub-prediction results. Secondly, a two-stage predictive model selection ... Dec 19, 2019 ... Abstract: Attribution methods provide insights into the decision-making of machine learning models like artificial neural networks. 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 ... Feb 22, 2023 ... We compare this control to a regularly-trained neural network, and show that perturbations on nodes carrying relay information cause failures in ...