Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques
GitHub - williamgilpin/convoca: Predict and analyze cellular automata using convolutional neural networks
![Generalization over different cellular automata rules learned by a deep feed-forward neural network: Paper and Code - CatalyzeX Generalization over different cellular automata rules learned by a deep feed-forward neural network: Paper and Code - CatalyzeX](https://www.catalyzex.com/_next/image?url=https%3A%2F%2Fai2-s2-public.s3.amazonaws.com%2Ffigures%2F2017-08-08%2Fc82879e047c97d8b13b942234e3347d3f3c39bd5%2F4-Figure1-1.png&w=640&q=75)
Generalization over different cellular automata rules learned by a deep feed-forward neural network: Paper and Code - CatalyzeX
![Ishay Rosenthal on Twitter: "Conway's Game of Life goes CRNN. Mordvintsev, et al. Using Convolutional Neural Networks to define the rules of Cellular Automata so that it (re)generates emojis. Lots of fun Ishay Rosenthal on Twitter: "Conway's Game of Life goes CRNN. Mordvintsev, et al. Using Convolutional Neural Networks to define the rules of Cellular Automata so that it (re)generates emojis. Lots of fun](https://pbs.twimg.com/media/ESoGp8pWoAAUcdH.png)
Ishay Rosenthal on Twitter: "Conway's Game of Life goes CRNN. Mordvintsev, et al. Using Convolutional Neural Networks to define the rules of Cellular Automata so that it (re)generates emojis. Lots of fun
![Sustainability | Free Full-Text | Integrating Cellular Automata with Unsupervised Deep-Learning Algorithms: A Case Study of Urban-Sprawl Simulation in the Jingjintang Urban Agglomeration, China Sustainability | Free Full-Text | Integrating Cellular Automata with Unsupervised Deep-Learning Algorithms: A Case Study of Urban-Sprawl Simulation in the Jingjintang Urban Agglomeration, China](https://pub.mdpi-res.com/sustainability/sustainability-11-02464/article_deploy/html/images/sustainability-11-02464-g001.png?1571441103)