Growing Neural Cellular Automata

1. 1Define the cellular automata model architecture
2. 2Implement the end-to-end differentiable training process
3. 3Train the model on specific patterns to enable growth and regeneration
4. 4Evaluate the model's performance on pattern generation and regeneration tasks

ML researchers and AI engineers can benefit from this concept to develop innovative models for pattern generation and regeneration, which can be applied in various fields such as computer vision and robotics

💡 End-to-end differentiable cellular automata models can be trained for self-organisation and pattern regeneration

🤖 Growing Neural Cellular Automata: training self-organising models for morphogenesis pattern growth & regeneration