A Functorial Formulation of Neighborhood Aggregating Deep Learning

We provide a mathematical interpretation of convolutional (or message passing) neural networks by using presheaves and copresheaves of the set of continuous functions over a topological space. Based on this interpretation, we formulate a theoretical heuristic which elaborates a number of empirical limitations of these neural networks by using obstructions on such sets of continuous functions over a topological space to be sheaves or copresheaves. --- Source: arXiv:2604.24672v1 - http://arxiv.org...