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49 search results found

Ampligraph ⭐ 1,963

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

Pretrain Gnns ⭐ 805

Strategies for Pre-training Graph Neural Networks

Compgcn ⭐ 519

ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks

Graphgps ⭐ 508

Recipe for a General, Powerful, Scalable Graph Transformer

Efficient Gnns ⭐ 490

Code and resources on scalable and efficient Graph Neural Networks

Graph Transformer ⭐ 408

Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

Mixhop And N Gcn ⭐ 389

An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

Graphgan ⭐ 381

A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)

Attentionwalk ⭐ 299

A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

Splitter ⭐ 203

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

Seal Ci ⭐ 201

A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)

Gnn Lspe ⭐ 114

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Official Pytorch code for Structure-Aware Transformer.

Source code for EvalNE, a Python library for evaluating Network Embedding methods.

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056

Inductive relation prediction by subgraph reasoning, ICML'20

3dinfomax ⭐ 64

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)

NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework

Embiggen ⭐ 35

🍇 Embiggen is the Python Graph Representation learning, Prediction and Evaluation submodule of the GRAPE library.

Graph Embedding via Frequent Subgraphs

Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)

[SIGIR'2023] "GFormer: Graph Transformer for Recommendation"

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)

Variational Graph Recurrent Neural Networks - PyTorch

Shift Robust Gnns ⭐ 24

"Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')

Neural Temporal Walks ⭐ 23

[NIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs"

Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert

Gated Graph Transformers ⭐ 19

Transformers are Graph Neural Networks!

TIP: Tri-graph Interaction Propagation model for Polypharmacy Side Eﬀect Prediction (GRL@NeurIPS, 2019)

[ICML'2023] "GraphST: Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"

Gnn Regvd ⭐ 14

Revisiting Graph Neural Networks for Vulnerability Detection (ICSE 2022) (Pytorch)

Metric Few Shot Graph ⭐ 13

Few-Shot Graph Classification via distance metric learning.

Subgraph Neural Networks (NeurIPS 2020)

This is the source code of "Network Embedding with Completely-Imbalanced Labels". TKDE2020

Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering

Taxonomy of Benchmarks in Graph Representation Learning

The code base for AWARE, a graph representation learning method published at TMLR

Rgcn Pytorch ⭐ 7

Pytorch implementation of Relational GCN for node classification

Permute Me Softly: Learning Soft Permutations for Graph Representations

Source code for our paper "Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation" (IJCAI 2020)

Graph Neural Networks for Knowledge Graph Link Prediction (WSDM 2022) (Pytorch)

Code for the ICDM 2019 Paper "RiWalk: Fast Structural Node Embedding via Role Identification".

Force2vec ⭐ 6

Implementation of Force2Vec method for ICDM 2020 paper titled "Force2Vec: Parallel force-directed graph embedding"

Connector ⭐ 5

The Graph Representation Learning Framework developed by NS Lab@CUK.

[PR 2021] Code for "GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction"

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