ConceptKAG / KAG框架
Kolmogorov-Arnold Geometry
Kolmogorov-Arnold Geometry is a theoretical framework for analyzing the internal computational structure of neural networks, particularly MLPs. It characterizes the local response of hidden layers to inputs through minors of the Jacobian matrix, in order to study the concentration of the network's local behavior.
Timeline (last 90 days)
Oct 19
The Kolmogorov-Arnold Geometry (KAG) framework reveals the internal computational structure of a network by analyzing the local response of hidden layers to input changes—that is, the minors of the Jacobian matrix.
Unverified50%