Goodfellow et al., Deep Learning

Mar 24, 2024 ... Graph neural networks (GNNs) have achieved state-of-the-art results on many graph representation learning tasks by exploiting statistical ... May 9, 2023 ... The article examines the role of the spontaneous activity of neurons, and therefore, of brain neural networks, in information processing. Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ... We propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma ... Just as the brain has interconnected neurons, a neural network has tiny interconnected nodes that work together to process information. Neural networks improve ... Dec 20, 2024 ... In ecosystems, financial markets, and neural networks, entropy fluctuates as new information reshapes the probability landscape. 4.2 The ... He also gives an example using a neural network class with fixed architecture as the hypothesis class. He is able to predict the qualitative effects of ... We present a review on the recent advances and emerging opportunities around the theme of analyzing deep neural networks (DNNs) with information-theoretic ... Jun 29, 2018 ... The brain has numerous levels of interaction ranging from gene networks that control cell function to neural circuits that control behavior. Sep 1, 2021 ... We find that specialized neuronal populations in auditory cortex form functional networks during auditory task performance whose structures depend on both ...