graph-representation-learning
There are 136 repositories under graph-representation-learning topic.
benedekrozemberczki/awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
naganandy/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
graphdeeplearning/benchmarking-gnns
Repository for benchmarking graph neural networks
Accenture/AmpliGraph
Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org
dsgiitr/graph_nets
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
snap-stanford/pretrain-gnns
Strategies for Pre-training Graph Neural Networks
tsinghua-fib-lab/GNN-Recommender-Systems
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
PyGCL/PyGCL
PyGCL: A PyTorch Library for Graph Contrastive Learning
acbull/pyHGT
Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
daiquocnguyen/Graph-Transformer
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
rampasek/GraphGPS
Recipe for a General, Powerful, Scalable Graph Transformer
malllabiisc/CompGCN
ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks
chaitjo/efficient-gnns
Code and resources on scalable and efficient Graph Neural Networks
hwwang55/GraphGAN
A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)
acbull/GPT-GNN
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
junxia97/awesome-pretrain-on-molecules
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
benedekrozemberczki/MixHop-and-N-GCN
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).
SXKDZ/awesome-self-supervised-learning-for-graphs
A curated list for awesome self-supervised learning for graphs.
benedekrozemberczki/AttentionWalk
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
CRIPAC-DIG/GRACE
[GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)
BorgwardtLab/SAT
Official Pytorch code for Structure-Aware Transformer.
vijaydwivedi75/gnn-lspe
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
dmlc/GNNLens2
Visualization tool for Graph Neural Networks
benedekrozemberczki/Splitter
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
benedekrozemberczki/SEAL-CI
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
kkteru/grail
Inductive relation prediction by subgraph reasoning, ICML'20
chaitjo/learning-tsp
Code for the paper 'Learning TSP Requires Rethinking Generalization' (CP 2021)
mims-harvard/SubGNN
Subgraph Neural Networks (NeurIPS 2020)
CRIPAC-DIG/GCA
[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"
zlpure/awesome-graph-representation-learning
A curated list for awesome graph representation learning resources.
HannesStark/3DInfomax
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
vijaydwivedi75/lrgb
Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
VGraphRNN/VGRNN
Variational Graph Recurrent Neural Networks - PyTorch
Dru-Mara/EvalNE
Source code for EvalNE, a Python library for evaluating Network Embedding methods.
JinheonBaek/GMT
Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)