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Keywords: Feedforward neural network, complexity, information complexity, neural complexity, radial basis functions, RBF networks, learning. 1. Introduction. Sep 10, 2019 ... Using a genetic algorithm approach to find optimal neural network structures for model-free policy learning in reinforcement learning; Using ... Aug 30, 2023 ... To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of 'Pong' to ... 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 ... same ink serve more than one informational purpose. Using large ... Physics-Informed Neural Networks for Anomaly Detection: A Practitioner's Guide ... We propose a novel neural network architecture which trains spatial positions of neural soma and axon pairs, where weights are calculated by axon-soma ... Apr 8, 2025 ... Neural networks are computational models that learn how to recognize patterns, develop predictions, and process data. By using algorithms, ... Dec 2, 2021 ... Each phase involves aligning the connections of the neural network with patterns of information contained in the input dataset or preceding ... The recent surge of graph embedding and graph neural networks also call for renewed and novel methodologies for heterogeneous information network analysis. As a ... Just as the brain has interconnected neurons, a neural network has tiny interconnected nodes that work together to process information. Neural networks improve ...