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distill.pub | ||
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xcorr.net
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| | | | | 2022 has come and gone and we've learned a lot about how the brain is - or isn't - like an artificial neural network. There isn't a single journal or venue that focuses exclusively on neuroAI so the literature is spread across preprint servers, conference proceedings and the occasional prestige journal. As an end-of-year treat,... | |
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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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markusmeister.com
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| | | | | My colleagues and I have been working through this intriguing paper [1] from a few weeks ago: Yan, G., Vértes, P.E., Towlson, E.K., Chew, Y.L., Walker, D.S., Schafer, W.R., and Barabási, A.-L. (2017). Network control principles predict neuron function in the Caenorhabditis elegans connectome. Nature advance online publication. This seems like a very important contribution.... | |
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www.v7labs.com
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| | | Learn about the different types of neural network architectures. | ||
