Weight-Space Mixture-of-Experts for Implicit Neural Representation Classification
This work proposes a hierarchical Mixture-of-Experts (HMoE) Transformer that processes INR weights using conditional computation aligned with the structure of the underlying implicit network and develops weight-space attribution and pruning methods that identify parameters most relevant for classification.