Forecasting

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 ... The semantic network ROI spanned a large swathe of heteromodal cortex, including most of the aforementioned cortical areas. The neural similarity structure of ... We do so by performing experiments on artificial neural networks in the context of fairness in machine learning, where the goal is to induce fairness in the ... 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 ... 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 ... Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts ... Feb 28, 2024 ... Intellectualization, cybersecurity, biometric image, deepfake, information technology, neural networks, detection system, instrumental platform, ... in the upper network level. Moreover, in a slightly different direction, research on multi-task learning neural networks, an approach aiming at internal ... Share your videos with friends, family, and the world. Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ...