architecture-generalization

This paper introduces Meta Neural Cellular Automata (MetaNCA), a framework that learns local update rules to self-organize the weights of neural networks without backpropagation, scaling to networks of 2 million parameters on MNIST and CIFAR-100 and generalizing to unseen architectures.