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#machine learning Preprint Sep 2026

Quantum Graph Convolutional Networks: Implementation and Trainability Analysis

This work implements two representative architectures --- the Simplified Graph Convolution (SGC) and Linear Graph Convolution (LGC) models and evaluates them on open benchmark graph datasets and semi-supervised learning tasks using quantum simulation and presents a cost gradient analysis that identifies the tasks for w...

Paul San Sebastian Sein, Theodor Iosif, T. G. Limbäck-Stokin et al. · 0 citations
Preprint Aug 2026

The Limits of Binding in Dual Encoders

Binding failure in deployed dual encoders is thus not a dimension or smoothness limit today, but an incentive and code-structure limit, with a proved depth ceiling that remains once those are fixed.

Kin Ian Lo · 0 citations

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