AlexNet

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 ... Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... 01/01/2024 Maryam Shanechi is elevated to IEEE Fellow. 12/11/2023 Our Nature Biomedical Engineering paper on neural network models with dynamical flexible ... May 9, 2023 ... The article examines the role of the spontaneous activity of neurons, and therefore, of brain neural networks, in information processing. Classically, external receptors of the body transmit information from the environment to the cerebral cortex via the thalamus. This review explains and ... 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. The semantic network ROI spanned a large swathe of heteromodal cortex, including most of the aforementioned cortical areas. The neural similarity structure of ... We then perform information le- sions of individual neurons to determine their contribution to each task. Following that, we investigate the ability of two. In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... ... system can become highly synergistic; and (b) how informational states map onto artificial neural networks in various learning modes. Here we employ an ...