An End-to-End Deep Learning Architecture for Graph Classification

Muhan Zhang; Zhicheng Cui; Marion Neumann; Yixin Chen

doi:https://doi.org/10.1609/aaai.v32i1.11782

An End-to-End Deep Learning Architecture for Graph Classification

2018 · Proceedings of the AAAI Conference on Artificial Intelligence · 1,519 citations · 4 from inside this corpus

Muhan Zhang low, Zhicheng Cui low, Marion Neumann low, Yixin Chen

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

12 of 12 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

this paper works it cites works citing it node size = global citations · hover for the full title

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

Graph neural networks: A review of methods and applications→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
A Comprehensive Survey on Graph Neural Networks→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
Deep Learning on Graphs: A Survey→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→An End-to-End Deep Learning Architecture for Graph ClassificationLegacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Efficient Estimation of Word Representations in Vector SpaceLegacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Libsvm : A library for support vector machinesLegacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→The Graph Neural Network ModelLegacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
An End-to-End Deep Learning Architecture for Graph Classification→Convolutional Neural Networks on Graphs with Fast Localized Spectral FilteringLegacy edge — source detail unavailable
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→Efficient Estimation of Word Representations in Vector SpaceLegacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→The Graph Neural Network ModelLegacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→Deep Learning on Graphs: A SurveyLegacy edge — source detail unavailable
Graph Neural Networks: A Review of Methods and Applications→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…→Efficient Estimation of Word Representations in Vector SpaceLegacy edge — source detail unavailable
Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…→The Graph Neural Network ModelLegacy edge — source detail unavailable
Deep Learning on Graphs: A Survey→The Graph Neural Network ModelLegacy edge — source detail unavailable
Deep Learning on Graphs: A Survey→Graph neural networks: A review of methods and applicationsLegacy edge — source detail unavailable
Graph neural networks: A review of methods and applications→The Graph Neural Network ModelLegacy edge — source detail unavailable
Graph neural networks: A review of methods and applications→Convolutional Neural Networks on Graphs with Fast Localized Spectral FilteringLegacy edge — source detail unavailable
Graph neural networks: A review of methods and applications→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
Graph neural networks: A review of methods and applications→A Comprehensive Survey on Graph Neural NetworksLegacy edge — source detail unavailable
A Comprehensive Survey on Graph Neural Networks→Spectral Networks and Locally Connected Networks on GraphsLegacy edge — source detail unavailable
A Comprehensive Survey on Graph Neural Networks→The Graph Neural Network ModelLegacy edge — source detail unavailable
A Comprehensive Survey on Graph Neural Networks→Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…Legacy edge — source detail unavailable
A Comprehensive Survey on Graph Neural Networks→Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…Legacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
Adam: A Method for Stochastic Optimization	2014	84,698
Efficient Estimation of Word Representations in Vector Space	2013	18,186
Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-…	2025	16,314
Libsvm : A library for support vector machines	2008	10,140
The Graph Neural Network Model	2008	9,662
Convolutional Neural Networks On Graphs With Fast Localized Spectral Filtering (Netsci-X'…	2016	5,118
Spectral Networks and Locally Connected Networks on Graphs	2013	2,726
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering	2016	1,703

What cites it, inside the corpus

Paper	Year	Cited
Graph neural networks: A review of methods and applications	2020	5,808
A Comprehensive Survey on Graph Neural Networks	2020	3,307
Deep Learning on Graphs: A Survey	2020	1,560
Graph Neural Networks: A Review of Methods and Applications	2018	1,448

Links

Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record

Topics

Advanced Graph Neural Networks	Computer Science
Big Data and Digital Economy	Computer Science
Graph Theory and Algorithms	Computer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

supports4 author record(s) attached.
supports53 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:58+00:00.

sha256 88a60cdbb94c6a13…