MatheusMRFM / NCA-GE
Implementation of the NCA-GE model from "Approximating Network Centrality Measures Using Node Embedding and Machine Learning"
☆11Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for NCA-GE
- ☆17Updated 8 months ago
- Testing link prediction using Node2Vec☆68Updated 7 years ago
- Dynamic graph/network dataset for dynamic graph/network embedding/representation☆32Updated 4 years ago
- Representation learning on dynamic graphs using self-attention networks☆282Updated last year
- Python 3 supported version for DySAT☆13Updated last year
- Final Project for Analysis of Network Data (CSE416a).☆9Updated 5 years ago
- WWW2020-One2Multi Graph Autoencoder for Multi-view Graph Clustering☆83Updated last year
- ☆128Updated last year
- Implementation of "Overlapping Community Detection with Graph Neural Networks"☆156Updated 4 years ago
- Code for "DyGCN: Dynamic Graph Embedding with Graph Convolutional Network"☆35Updated 7 months ago
- Source code from the CIKM 2019 article "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" by G. Salha, S. Limnios, R. Hen…☆44Updated 11 months ago
- PyTorch_Geometric实现的JK-Nets(Jumping Knowledge Network),其中也包括了baseline的GCN和GAT。数据集使用的「Cora、Citeseer、Pubmed」☆15Updated 3 years ago
- CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/…☆95Updated last year
- An implementation of paper: Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding☆17Updated 3 years ago
- PyTorch implementation of Deep Attention Embedding Graph Clustering (19IJCAI) https://www.ijcai.org/Proceedings/2019/0509.pdf☆108Updated 3 years ago
- ☆75Updated 2 years ago
- Pytorch implementation of various Graph Neural Networks (GNNs) for graph classification☆100Updated 4 years ago
- Implementation in TF2 of Community-Centric Graph Convolutional Network for Unsupervised Community Detection☆19Updated 2 years ago
- ☆298Updated 4 months ago
- Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).☆52Updated last month
- Data repository for PyGOD☆38Updated 9 months ago
- Graph Attention Auto-Encoders☆73Updated last year
- Learning Deep Representations for Graph Clustering Implementation☆18Updated 5 years ago
- ☆48Updated 3 years ago
- ☆51Updated 4 years ago
- Pytorch implementation of DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks☆82Updated 2 years ago
- CDBNE☆13Updated 2 years ago
- Heterogeneous Hypergraph Variational Autoencoder for Link Prediction (T-PAMI 2021)☆31Updated 3 years ago
- A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks"…☆121Updated 2 years ago
- Source code and dataset for KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"☆109Updated last year