Learnable magnetic spectral PEs of the form h_θ(A_q)R, computed in Hermitian block Krylov subspaces, are eigenbasis-independent, O(log 1/ε)-approximable for heat–resolvent families, and recover directed structure where symmetrized baselines fail.
The Eleventh International Conference on Learning Representations , year=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Eigenbasis-Independent Learnable Spectral Positional Encodings for Directed Graphs via Hermitian Block Krylov Subspaces
Learnable magnetic spectral PEs of the form h_θ(A_q)R, computed in Hermitian block Krylov subspaces, are eigenbasis-independent, O(log 1/ε)-approximable for heat–resolvent families, and recover directed structure where symmetrized baselines fail.