# Deep Graph Similarity Learning: A Survey

arXiv: https://arxiv.org/abs/1912.11615 · HTML: https://mlsanity.com/paper/1912.11615/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Dec 2019.

## Built on by (most cited first, 19 of 19)

- [Parameter Prediction for Unseen Deep Architectures](https://mlsanity.com/paper/2110.13100/) (2021)
- [Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model](https://mlsanity.com/paper/2207.07650/) (2022)
- [Graph similarity learning for change-point detection in dynamic networks](https://mlsanity.com/paper/2203.15470/) (2022)
- [Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression](https://mlsanity.com/paper/2205.15858/) (2022)
- [An embedding-based distance for temporal graphs](https://mlsanity.com/paper/2401.12843/) (2024)
- [Graph Similarity Description: How Are These Graphs Similar?](https://mlsanity.com/paper/2105.14364/) (2021)
- [Memory-Augmented Graph Neural Networks: A Brain-Inspired Review](https://mlsanity.com/paper/2209.10818/) (2022)
- [Privacy-Preserved Neural Graph Similarity Learning](https://mlsanity.com/paper/2210.11730/) (2022)
- [Shape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysis](https://mlsanity.com/paper/2308.06869/) (2023)
- [Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets](https://mlsanity.com/paper/2402.15524/) (2024)
- [LayoutGKN: Graph Similarity Learning of Floor Plans](https://mlsanity.com/paper/2509.03737/) (2025)
- [Operator Autoencoders: Learning Physical Operations on Encoded Molecular Graphs](https://mlsanity.com/paper/2105.12295/) (2021)
- [Interactive Visual Pattern Search on Graph Data via Graph Representation Learning](https://mlsanity.com/paper/2202.09459/) (2022)
- [Beyond MMD: Evaluating Graph Generative Models with Geometric Deep Learning](https://mlsanity.com/paper/2512.14241/) (2025)
- [A Deep Learning Framework for Evaluating Dynamic Network Generative Models and Anomaly Detection](https://mlsanity.com/paper/2406.11901/) (2024)
- [GSpect: Spectral Filtering for Cross-Scale Graph Classification](https://mlsanity.com/paper/2409.00338/) (2024)
- [ICGM-FRAX: Iterative Cross Graph Matching for Hip Fracture Risk Assessment using Dual-energy X-ray Absorptiometry Images](https://mlsanity.com/paper/2504.15384/) (2025)
- [Predicting Graph Structure via Adapted Flux Balance Analysis](https://mlsanity.com/paper/2507.05806/) (2025)
- [GMN4AD: Graph Matching Network for Alzheimer's Disease Diagnosis with Test-Time Domain Adaptation using Multi-centered Structure Magnetic Resonance Imaging](https://mlsanity.com/paper/2606.13919/) (2026)

## Abstract (arXiv)

In many domains where data are represented as graphs, learning a similarity metric among graphs is considered a key problem, which can further facilitate various learning tasks, such as classification, clustering, and similarity search. Recently, there has been an increasing interest in deep graph similarity learning, where the key idea is to learn a deep learning model that maps input graphs to a target space such that the distance in the target space approximates the structural distance in the input space. Here, we provide a comprehensive review of the existing literature of deep graph similarity learning. We propose a systematic taxonomy for the methods and applications. Finally, we discuss the challenges and future directions for this problem.