Focusing on Relevant Information

Neural networks integrating information and primary reward. Early neuroscience studies of information seeking in monkeys focused on the “reward prediction error ... ... information theory in the evaluation of single neuron responses and neural networks. The question of the neural code has been debated heatedly since the ... Mar 24, 2024 ... Graph neural networks (GNNs) have achieved state-of-the-art results on many graph representation learning tasks by exploiting statistical ... Graph neural networks (GNNs) have achieved state-of-the- art performance in graph representation learning by exploit- ing statistical correlations. However, ... Essentially, the network learns how to learn, and that is a really puzzling result. 30th Conference on Neural Information Processing Systems (NIPS 2016), ... Feb 25, 2025 ... Neurons are responsible for sending and receiving neurotransmitters—chemicals that carry information between brain cells. Depending on its ... Jun 29, 2018 ... The brain has numerous levels of interaction ranging from gene networks that control cell function to neural circuits that control behavior. Feb 26, 2024 ... This article introduces a quantitative approach to modeling the cost of control in a neural network architecture when it is required to execute one or more ... Share your videos with friends, family, and the world. Abstract. The concept of Learning by Stimulus Avoidance (LSA) has been proposed in recent literature, and the methods of avoiding stimuli: action, prediction, ...