Categorical Deep Learning: An Algebraic Theory of Architectures

arXiv:2402.15332v1 Announce Type: new
Abstract: We present our position on the elusive quest for a general-purpose framework for specifying and studying deep learning architectures. Our opinion is that the key attempts made so far lack a coherent bridge between specifying constraints which models must satisfy and specifying their implementations. Focusing on building a such a bridge, we propose to apply category theory -- precisely, the universal algebra of monads valued in a 2-category of parametric maps -- as a single …

abstract architectures arxiv bridge building categorical constraints cs.ai cs.lg deep learning framework general key opinion quest stat.ml studying the key theory type