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Jiho Choi

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#machine learning Preprint Jan 2026

Persistent Tri-State Message Passing

Permuting complete weight vectors between samples quantifies the same role-state dependence while preserving their empirical distribution in Persistent Tri-State Message Passing, which combines persistent additive, subtractive, and inactive roles with weights computed from each sample's endpoint states.

Y. Choi, Ji-Ho Choi, Chong-kwon Kim · 0 citations
Aug 2026

Uncertainty-Aware Adaptive Edge Blocking in Heterophilic Graph Neural Networks

This work provides theoretical guarantees for the selective blocking rule by deriving the signed-versus-blocked decision boundary, separating signed-matrix effects from nonnegative block-operator spectral arguments, and showing when adaptive blocking preserves class-dependent components.

Ji-Ho Choi, Yu-Min Lee, Chanran Kim et al. · 0 citations

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