# Quantum Link Prediction in Complex Networks

arXiv: https://arxiv.org/abs/2112.04768 · HTML: https://mlsanity.com/paper/2112.04768/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Dec 2021.

## Built on by (most cited first, 5 of 5)

- [Link prediction with continuous-time classical and quantum walks](https://mlsanity.com/paper/2208.11030/) (2022)
- [Network-based link prediction of scientific concepts -- a Science4Cast competition entry](https://mlsanity.com/paper/2201.07978/) (2022)
- [Disease Gene Prioritization With Quantum Walks](https://mlsanity.com/paper/2311.05486/) (2023)
- [QSearchNet: A Quantum Walk Search Framework for Link Prediction](https://mlsanity.com/paper/2510.00325/) (2025)
- [A2QTGN: Adaptive Amplitude Quantum-Integrated Temporal Graph Network for Dynamic Link Prediction](https://mlsanity.com/paper/2605.21916/) (2026)

## Abstract (arXiv)

Predicting new links in physical, biological, social, or technological networks has a significant scientific and societal impact. Path-based link prediction methods utilize explicit counting of even and odd-length paths between nodes to quantify a score function and infer new or unobserved links. Here, we propose a quantum algorithm for path-based link prediction, QLP, using a controlled continuous-time quantum walk to encode even and odd path-based prediction scores. Through classical simulations on a few real networks, we confirm that the quantum walk scoring function performs similarly to other path-based link predictors. In a brief complexity analysis we identify the potential of our approach in uncovering a quantum speedup for path-based link prediction.