图神经网络上百篇论文分类整理

Posted 2021-12-17 人工智能博士

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今天分享一份高赞的图神经网络的学习资源，里面整理了大量图深度学习论文，大多数都被顶会收录，数量有上百篇。这份资源最闪亮的地方，就是将这些不同方向已经发表的论文进行了整理，分门别类得放上了论文的标题、作者、关键词和地址链接。

本文整理了近期研究火热的“图”神经网络相关资源，包括节点的表示学习、知识图谱编码、图神经网络、图神经网络的应用、图生成、图的可视化、图表示学习的系统等。

目录

1.   Node Representation Learning

    1.1   Unsupervised Node Representation Learning

    1.2   Node Representation Learning in Heterogeneous Graphs

    1.3   Node Representation Learning in Dynamic Graphs

2.   Knowledge Graph Embedding

3.   Graph Neural Networks

4.   Applications of Graph Deep Learning

    4.1   Natural Language Processing

    4.2   Computer Vision

    4.3   Recommender Systems

    4.4   Link Prediction

    4.5   Influence Prediction

    4.6   Neural Architecture Search

    4.7   Reinforcement Learning

    4.8   Combinatorial Optimization

    4.9   Adversarial Attack and Robustness

    4.10   Meta Learning and Few-shot Learning

    4.11   Structure Learning

    4.12   Bioinformatics and Chemistry

    4.13   Theorem Proving

5.   Graph Generation

6.   Graph Layout and High-dimensional Data Visualization

7.   Graph Representation Learning Systems

8.   Datasets

1. Node Representation Learning

1.1 Unsupervised Node Representation Learning

经典论文：

DeepWalk: Online Learning of Social Representations KDD 2014 

LINE: Large-scale Information Network Embedding WWW 2015

GraRep: Learning Graph Representations with Global Structural Information CIKM 2015

node2vec: Scalable Feature Learning for Networks KDD 2016

近期论文：

arXiv 1611 Variational Graph Auto-Encoders

AAAI 2017 Scalable Graph Embedding for Asymmetric Proximity

IJCAI 2017 Fast Network Embedding Enhancement via High Order Proximity Approximation

KDD 2017 struc2vec: Learning Node Representations from Structural Identity

NIPS 2017 Poincaré Embeddings for Learning Hierarchical Representations

WWW 2018 VERSE: Versatile Graph Embeddings from Similarity Measures

WSDM 2018 Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

KDD 2018 Learning Structural Node Embeddings via Diffusion Wavelets

AAAI 2018 Adversarial Network Embedding

GraphGAN: Graph Representation Learning with Generative Adversarial Nets

WSDM 2019 A General View for Network Embedding as Matrix Factorization

ICLR 2019 Deep Graph Infomax

WWW 2019 NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization Adversarial Training Methods for Network Embedding

1.2 Node Representation Learning in Heterogeneous Graphs

WSDM 2014 Learning Latent Representations of Nodes for Classifying in Heterogeneous Social Networks Jian Tang, Meng Qu, Qiaozhu Mei

KDD 2015 PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks Heterogeneous Network Embedding via Deep Architectures

AAAI 2015 Network Representation Learning with Rich Text Information

IJCAI 2016 Max-Margin DeepWalk: Discriminative Learning of Network Representation

KDD 2017 metapath2vec: Scalable Representation Learning for Heterogeneous Networks

arXiv 2016 Meta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks

CIKM 2017 HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning

An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Multi-view Clustering with Graph Embedding for Connectome Analysis

Attributed Signed Network Embedding

ACL 2017 CANE: Context-Aware Network Embedding for Relation Modeling

KDD 2018 PME: Projected Metric Embedding on Heterogeneous Networks for Link Prediction

Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

SIGIR 2018 BiNE: Bipartite Network Embedding

AAAI 2018 StarSpace: Embed All The Things

AAAI 2018 Generative Adversarial Network based Heterogeneous Bibliographic Network Representation for Personalized Citation Recommendation

AAAI 2018 ANRL: Attributed Network Representation Learning via Deep Neural Networks

WSDM 2018 Exploring Expert Cognition for Attributed Network Embedding

WSDM 2018 SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction

WSDM 2018 Multidimensional Network Embedding with Hierarchical Structures

WSDM 2018 Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning

IJCAI 2018 Efficient Attributed Network Embedding via Recursive Randomized Hashing

IJCAI 2018 Deep Attributed Network Embedding

WWW 2018 Co-Regularized Deep Multi-Network Embedding

ICDM 2018 Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights

WWW 2018 SIDE: Representation Learning in Signed Directed Networks

1.3 Node Representation Learning in Dynamic Graphs

ICML 2017 Know-evolve: Deep temporal reasoning for dynamic knowledge graphs

ICLR 2017 Workshop Dyngem: Deep embedding method for dynamic graphs

CIKM 2017 Attributed network embedding for learning in a dynamic environment

AAAI 2018 Dynamic Network Embedding by Modeling Triadic Closure Process

DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks

TIMERS: Error-Bounded SVD Restart on Dynamic Networks

KDD 2018 Dynamic Embeddings for User Profiling in Twitter

IJCAI 2018 Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding

ICLR 2019 DyRep: Learning Representations over Dynamic Graphs 

2. Knowledge Graph Embedding

NIPS 2013 Translating Embeddings for Modeling Multi-relational Data

AAAI 2014 Knowledge Graph Embedding by Translating on Hyperplanes

AAAI 2015 Learning Entity and Relation Embeddings for Knowledge Graph Completion

ACL 2015 Knowledge Graph Embedding via Dynamic Mapping Matrix

EMNLP 2015 Modeling Relation Paths for Representation Learning of Knowledge Bases

ICLR 2015 Embedding Entities and Relations for Learning and Inference in Knowledge Bases

AAAI 2016 Holographic Embeddings of Knowledge Graphs

ICML 2016 Complex Embeddings for Simple Link Prediction

arXiv 2017.03 Modeling Relational Data with Graph Convolutional Networks

arXiv 2017.10 Fast Linear Model for Knowledge Graph Embeddings

AAAI 2018 Convolutional 2D Knowledge Graph Embeddings

Knowledge Graph Embedding With Iterative Guidance From Soft Rules

NAACL 2018 KBGAN: Adversarial Learning for Knowledge Graph Embeddings

A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network

ACL 2018 Improving Knowledge Graph Embedding Using Simple Constraints

NeurIPS 2018 SimplE Embedding for Link Prediction in Knowledge Graphs

WWW 2019 Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

ICLR 2019 RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

ACL 2019 Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

3. Graph Neural Networks

ICML 2016 Revisiting Semi-supervised Learning with Graph Embeddings

ICLR 2017 Semi-Supervised Classification with Graph Convolutional Networks

ICML 2017 Neural Message Passing for Quantum Chemistry

IJCAI 2017 Motif-Aware Graph Embeddings

NIPS 2017 Learning Graph Representations with Embedding Propagation

Inductive Representation Learning on Large Graphs

ICLR 2018 Graph Attention Networks

FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

ICML 2018 Representation Learning on Graphs with Jumping Knowledge Networks

Stochastic Training of Graph Convolutional Networks with Variance Reduction

KDD 2018 Large-Scale Learnable Graph Convolutional Networks

Adaptive Sampling Towards Fast Graph Representation Learning

Hierarchical Graph Representation Learning with Differentiable Pooling

Bayesian Semi-supervised Learning with Graph Gaussian Processes

arXiv 2018.11 Pitfalls of Graph Neural Network Evaluation

WWW 2019 Heterogeneous Graph Attention Network

ICLR 2019 How Powerful are Graph Neural Networks?

LanczosNet: Multi-Scale Deep Graph Convolutional Networks

Graph Wavelet Neural Network

Supervised Community Detection with Line Graph Neural Networks

Predict then Propagate: Graph Neural Networks meet Personalized PageRank

Invariant and Equivariant Graph Networks

Capsule Graph Neural Network

ICML 2019 MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing Graph U-Nets

Disentangled Graph Convolutional Networks

GMNN: Graph Markov Neural Networks

Simplifying Graph Convolutional Networks

Position-aware Graph Neural Networks

Self-Attention Graph Pooling

4. Applications of Graph Neural Networks

4.1 Natural Language Processing

EMNLP 2017 Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

Graph Convolutional Encoders for Syntax-aware Neural Machine Translation

CoNLL 2017 Graph-based Neural Multi-Document Summarization

ICLR 2018 QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

ICLR 2018 A Structured Self-attentive Sentence Embedding

COLING 2018 Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering

NAACL 2018 Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks

EMNLP 2018 Linguistically-Informed Self-Attention for Semantic Role Labeling

Graph Convolution over Pruned Dependency Trees Improves Relation Extraction

ACL 2018 A Graph-to-Sequence Model for AMR-to-Text Generation Graph-to-Sequence Learning using Gated Graph Neural Networks

AAAI 2019 Graph Convolutional Networks for Text Classification Multi-task Learning over Graph Structures

ICLR 2019. Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder Structured Neural Summarization

NAACL 2019 Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

Single Document Summarization as Tree Induction

Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks

ACL 2019 Graph Neural Networks with Generated Parameters for Relation Extraction

Dynamically Fused Graph Network for Multi-hop Reasoning

Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media

Attention Guided Graph Convolutional Networks for Relation Extraction

Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction

Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs

Cognitive Graph for Multi-Hop Reading Comprehension at Scale Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model

Matching Article Pairs with Graphical Decomposition and Convolutions Embedding Imputation with Grounded Language Information

WWW 2019 Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations

4.2 Computer Vision

ICCV 2017 3D Graph Neural Networks for RGBD Semantic Segmentation

Situation Recognition With Graph Neural Networks

Graph-Based Classification of Omnidirectional Images

AAAI 2018 Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

CVPR 2018 Image Generation from Scene Graphs

FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation

PPFNet: Global Context Aware Local Features for Robust 3D Point Matching

Iterative Visual Reasoning Beyond Convolutions Surface Networks

FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis

Learning to Act Properly: Predicting and Explaining Affordances From Images

Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling

Deformable Shape Completion With Graph Convolutional Autoencoders

ECCV 2018 Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

Learning Human-Object Interactions by Graph Parsing Neural Networks

Generating 3D Faces using Convolutional Mesh Autoencoders

Neural Graph Matching Networks for Fewshot 3D Action Recognition

Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds

Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network

Graph R-CNN for Scene Graph Generation

Exploring Visual Relationship for Image Captioning Beyond Grids: Learning Graph Representations for Visual Recognition

Learning Conditioned Graph Structures for Interpretable Visual Question Answering

LinkNet: Relational Embedding for Scene Graph Flexible Neural Representation for Physics Prediction

ICLR 2019 Learning Localized Generative Models for 3D Point Clouds via Graph Convolution

CVPR 2019 Graph-Based Global Reasoning Networks

Deep Graph Laplacian Regularization for Robust Denoising of Real Images

Learning Context Graph for Person Search

Graphonomy: Universal Human Parsing via Graph Transfer Learning

Masked Graph Attention Network for Person Re-Identification

Learning to Cluster Faces on an Affinity Graph

Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition

Adaptively Connected Neural Networks

4.3 Recommender Systems

KDD 2018 Graph Convolutional Neural Networks for Web-Scale RecommenderSystems

AAAI 2018 SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation

WSDM 2019 Session-based Social Recommendation via Dynamic Graph Attention Networks

WWW 2019 Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems

Graph Neural Networks for Social Recommendation

AAAI 2019 Session-based Recommendation with Graph Neural Networks

SIGIR 2019 A Neural Influence Diffusion Model for Social Recommendation

Neural Graph Collaborative Filtering

IJCAI 2019 Binarized Collaborative Filtering with Distilling Graph Convolutional Networks

4.4 Link Prediction

Link Prediction Based on Graph Neural Networks

AAAI 2018 Link Prediction via Subgraph Embedding-Based Convex Matrix Completion

KDD 2018 Workshop Graph Convolutional Matrix Completion

4.5 Influence Prediction

KDD 2018 DeepInf: Social Influence Prediction with Deep Learning

KDD 2019 Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

4.6 Neural Architecture Search

ICLR 2019 Graph HyperNetworks for Neural Architecture Search

4.7 Reinforcement Learning

AAAI 2018 Action Schema Networks: Generalised Policies with Deep Learning

ICLR 2018 NerveNet: Learning Structured Policy with Graph Neural Networks

ICML 2018 Graph Networks as Learnable Physics Engines for Inference and Control

Learning Policy Representations in Multiagent Systems

Relational recurrent neural networks

Transfer of Deep Reactive Policies for MDP Planning

ICLR 2019 Neural Graph Evolution: Towards Efficient Automatic Robot Design

4.8 Combinatorial Optimization

Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search

Reinforcement Learning for Solving the Vehicle Routing Problem

4.9 Adversarial Attack

ICML 2018 Adversarial Attack on Graph Structured Data

KDD 2018 Adversarial Attacks on Neural Networks for Graph Data

ICLR 2019 Adversarial Attacks on Graph Neural Networks via Meta Learning

4.10 Meta Learning

ICML 2018 Learning Steady-States of Iterative Algorithms over Graphs

4.11 Structure Learning

ICLR 2018 Few-Shot Learning with Graph Neural Networks

ICML 2018 Neural Relational Inference for Interacting Systems

arXiv 19 Brain Signal Classification via Learning Connectivity Structure

A Flexible Generative Framework for Graph-based Semi-supervised Learning

Joint embedding of structure and features via graph convolutional networks

Variational Spectral Graph Convolutional Networks

ICLR 2019 Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

ICML 2019 Workshop Graph Learning Network: A Structure Learning Algorithm

ICML 2019 Learning Discrete Structures for Graph Neural Networks

Graphite: Iterative Generative Modeling of Graphs

4.12 Bioinformatics

NeurIPS 2017 Protein Interface Prediction using Graph Convolutional Networks

Bioinformatics 2018 Modeling polypharmacy side effects with graph convolutional networks

NeoDTI: neural integration of neighbor information from a heterogeneous network for discovering new drug–target interactions

4.13 Theorem Proving

Premise Selection for Theorem Proving by Deep Graph Embedding

Graph Generation

ICML 2018 GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

NetGAN: Generating Graphs via Random Walks

Junction Tree Variational Autoencoder for Molecular Graph Generation

arXiv 1805 MolGAN: An implicit generative model for small molecular graphs

Generative Modeling for Protein Structures

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

Constrained Graph Variational Autoencoders for Molecule Design

ICLR 2019 Learning Multimodal Graph-to-Graph Translation for Molecule Optimization

DAG-GNN: DAG Structure Learning with Graph Neural Networks

AISTATS 2019 Graph to Graph: a Topology Aware Approach for Graph Structures Learning and Generation

Graph Layout and High-dimensional Data Visualization

JMLR 2008 Visualizing Data using t-SNE

ML 2012 Visualizing non-metric similarities in multiple maps

WWW 2016 Visualizing Large-scale and High-dimensional Data Graph Representation Learning Systems

WWW 2019 GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding

SysML 2019 PyTorch-BigGraph: A Large-scale Graph Embedding System

VLDB 2019 AliGraph: A Comprehensive Graph Neural Network Platform

DGL Team Deep Graph Library

Alimama Engineering Platform Team, Alimama Search Advertising Algorithm Team Euler

5.   Graph Generation

ICML 2018 GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

ICML 2018 NetGAN: Generating Graphs via Random Walks

ICML 2018 Learning Deep Generative Models of Graphs

ICML 2018 Junction Tree Variational Autoencoder for Molecular Graph Generation

arXiv 2018 MolGAN: An implicit generative model for small molecular graphs

NeurIPS 2018 Generative Modeling for Protein Structures

NeurIPS 2018 Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

NeurIPS 2018 Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

NeurIPS 2018 Constrained Graph Variational Autoencoders for Molecule Design

ICLR 2019 Learning Multimodal Graph-to-Graph Translation for Molecule Optimization

ICLR 2019 Generative Code Modeling with Graphs

ICML 2019 DAG-GNN: DAG Structure Learning with Graph Neural Networks

AISTATS 2019 Graph to Graph: a Topology Aware Approach for Graph Structures Learning and Generation

NeurIPS 2019 Graph Normalizing Flows

NeurIPS 2019 Conditional Structure Generation through Graph Variational Generative Adversarial Nets

NeurIPS 2019 Efficient Graph Generation with Graph Recurrent Attention Networks

ICLR 2020 GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

6.   Graph Layout and High-dimensional Data Visualization

JMLR 2008 Visualizing Data using t-SNE

ML 2012 Visualizing non-metric similarities in multiple maps

WWW 2016 Visualizing Large-scale and High-dimensional Data

ICLR 2019 Workshop GraphTSNE: A Visualization Technique for Graph-Structured Data

7.   Graph Representation Learning Systems

WWW 2019 GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding

SysML 2019 PyTorch-BigGraph: A Large-scale Graph Embedding System

VLDB 2019 AliGraph: A Comprehensive Graph Neural Network Platform

8.   Datasets

AAAI 2019 ATOMIC: an atlas of machine commonsense for if-then reasoning

9. Github链接

https://github.com/DeepGraphLearning/LiteratureDL4Graph

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