Learning from Incomplete Episodes

Machine Learning, Deep Learning, Naïve Bayes, Feature Engineering, Identifying Informative Tweets. INTRODUCTION. In recent years, micro-blogging services such ... ... information theory in the evaluation of single neuron responses and neural networks. The question of the neural code has been debated heatedly since the ... The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar is a very interdisciplinary work. Anyone interested in the ... Sep 4, 2023 ... ... neuronal networks or whether it is related to informational load. ... To explore this topic, we used an in vitro neural network of cortical ... In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ... classification via convolutional deep neural network. In Proceedings of COLING. 2014, the 25th International Conference on Computational Linguistics ... May 29, 2024 ... However, in large systems, such as neuronal networks, the reconstruction of such topology is usually carried out from the information encoded in ... The semantic network ROI spanned a large swathe of heteromodal cortex, including most of the aforementioned cortical areas. The neural similarity structure of ... Jan 9, 2024 ... 43. Francis, N.A. ... Sequential transmission of task-relevant information in cortical neuronal networks. Cell Rep. 2022; 39, 110878.