Image Augmentation

Neural networks integrating information and primary reward. Early neuroscience studies of information seeking in monkeys focused on the “reward prediction error ... In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... Just as the brain has interconnected neurons, a neural network has tiny interconnected nodes that work together to process information. Neural networks improve ... Neural Networks, pp. 271–280. RESEARCH IN PROGRESS. • “Seller-Provided Information and Return Policies for Experience Goods,” under review at. Decision ... Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts ... Sep 22, 2020 ... By recruiting adjacent neurons into oscillations, waves of synchronously firing neuronal networks—and thereby conscious thoughts—can travel ... Apr 8, 2025 ... Neural networks are computational models that learn how to recognize patterns, develop predictions, and process data. By using algorithms, ... Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ... Mar 24, 2024 ... Graph neural networks (GNNs) have achieved state-of-the-art results on many graph representation learning tasks by exploiting statistical ... Dec 31, 2022 ... We relax these limitations using deep learning methods. We use a neural network to classify insurees into joint choice of coverage and claim ...