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www.michelecoscia.com | ||
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blog.otoro.net
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| | | | | [AI summary] This article describes a project that combines genetic algorithms, NEAT (NeuroEvolution of Augmenting Topologies), and backpropagation to evolve neural networks for classification tasks. The key components include: 1) Using NEAT to evolve neural networks with various activation functions, 2) Applying backpropagation to optimize the weights of these networks, and 3) Visualizing the results of the evolved networks on different datasets (e.g., XOR, two circles, spiral). The project also includes a web-based demo where users can interact with the system, adjust parameters, and observe the evolution process. The author explores how the genetic algorithm can discover useful features (like squaring inputs) without human intervention, and discusses the ... | |
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bastian.rieck.me
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| | | | | [AI summary] The author explores the application of social network analysis to Shakespeare's plays, examining character interactions and graph density to uncover patterns in different play types. | |
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faculty.ucr.edu
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golb.hplar.ch
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| | | [AI summary] The article describes the implementation of a neural network in Java and JavaScript for digit recognition using the MNIST dataset, covering forward and backpropagation processes. | ||
