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Effective Resistance and Graph Neural Network Reliability in Tissue-Specific Interactomes

Paper recorded by Signals 4 on 2026-10-01 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-01 on arXiv · recorded by Signals 4 on 2026-10-02

Category: cs.LG · 机器学习 · first seen 2026-10-02

Abstract

Protein function annotation needs to know which predictions to distrust, not only what a model predicts. We ask whether tissue-specific interaction structure carries that information. Our candidate signal is effective resistance, used previously to relieve over-squashing by rewiring. Across 24 tissue-specific interactomes it is dominated by inverse degree, and the degeneration deepens as the co-ex

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#9 most recent of 362 cs.LG papers we have recorded · ↑ newer: From Gradients to Capabilities: Understanding Multi-Teacher On-Policy · ↓ older: Every Ablation Is a Dose: Counterweights and the Semblance of Self-Rep
Cite this page: Effective Resistance and Graph Neural Network Reliability in Tissue-Specific Interactomes: the #9 most recent of 362 cs.LG papers we have recorded (as of 2026-10-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/effective-resistance-and-graph-neural-network-reliability-in-tissue-specific-int.html
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