LiZhang-github / Graph-Representation-Learning

Graph Representation Learning

2019 top conference papers for Graph Neural Networks (updating)

ICML2019

Adversarial Attacks on Node Embeddings via Graph Poisoning https://arxiv.org/pdf/1809.01093.pdf

Learning Discrete Structures for Graph Neural Networks https://arxiv.org/pdf/1903.11960.pdf

MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing https://arxiv.org/pdf/1905.00067.pdf

Graph markov neural networks https://arxiv.org/pdf/1905.06214.pdf

Disentangled Graph Convolutional Networks http://pengcui.thumedialab.com/papers/DisenGCN.pdf

Position-aware Graph Neural Networks http://proceedings.mlr.press/v97/you19b/you19b.pdf

ICLR2019

Adversarial Attacks on Graph Neural Networks via Meta Learning https://openreview.net/forum?id=Bylnx209YX

Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs https://openreview.net/forum?id=BJluy2RcFm

LanczosNet: Multi-Scale Deep Graph Convolutional Networks http://www.cs.toronto.edu/~rjliao/papers/NIPS_R2L_lanczos_net.pdf

Predict then Propagate: Graph Neural Networks meet Personalized PageRank https://openreview.net/forum?id=H1gL-2A9Ym

Wasserstein weisfeiler-lehman graph kernels https://arxiv.org/pdf/1906.01277.pdf

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space https://openreview.net/forum?id=HkgEQnRqYQ

HOW POWERFUL ARE GRAPH NEURAL NETWORKS? https://cs.stanford.edu/people/jure/pubs/gin-iclr19.pdf

WWW/KDD 2019

Session-based Social Recommendation via Dynamic Graph Attention Networks https://arxiv.org/pdf/1902.09362.pdf

Heterogeneous Graph Attention Network https://arxiv.org/pdf/1903.07293.pdf

Dual Graph Atention Networks for Deep Latent Representation of Multifaceted Social E�ects in Recommender Systems https://arxiv.org/pdf/1903.10433.pdf

KGAT: Knowledge Graph Attention Network for Recommendation https://arxiv.org/pdf/1905.07854.pdf

Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems https://arxiv.org/pdf/1905.04413.pdf

Robust Graph Convolutional Networks Against Adversarial Attacks http://pengcui.thumedialab.com/papers/RGCN.pdf

Graph Neural Networks for Social Recommendation https://arxiv.org/pdf/1902.07243.pdf

CVPR2019

Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition https://arxiv.org/pdf/1904.12659.pdf

An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition https://arxiv.org/pdf/1902.09130.pdf

Linkage Based Face Clustering via Graph Convolution Network https://arxiv.org/pdf/1903.11306.pdf

Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning https://arxiv.org/pdf/1904.02113.pdf

Some important papers

Recommend papers on NRL/NE

https://github.com/thunlp/NRLPapers

Awesome-network-embedding

https://github.com/chihming/awesome-network-embedding/blob/master/README.md

geometric-deep-learning-literature

https://github.com/naganandy/geometric-deep-learning-literature/blob/master/conference-journal-articles/README.md

Graph-based Neural Networks

https://github.com/sungyongs/graph-based-nn

Good slides

Structured deep models:Deep learning on graphs and beyond

http://tkipf.github.io/misc/SlidesCambridge.pdf

www-18 Tutorial Representation Learning on Networks

http://snap.stanford.edu/proj/embeddings-www/

Overview of neural network architectures for graph-structured data analysis

http://www.cl.cam.ac.uk/~pv273/slides/UCLGraph.pdf

Graph Data

LINQS Statistical Relational Learning Group

https://linqs.soe.ucsc.edu/data

Stanford Large Network Dataset Collection

http://snap.stanford.edu/data/

Important package:

Geometric Deep Learning Extension Library for PyTorch

https://github.com/rusty1s/pytorch_geometric

An open source toolkit for Network Embedding

https://github.com/thunlp/openne

Tools for analyzing graph

https://gephi.org/users/quick-start/