rctzeng / ICML19-EgoCNNLinks
Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)
☆20Updated 3 years ago
Alternatives and similar repositories for ICML19-EgoCNN
Users that are interested in ICML19-EgoCNN are comparing it to the libraries listed below
Sorting:
- Laplacian Change Point Detection for Dynamic Graphs (KDD 2020)☆29Updated 2 years ago
- Graph Recurrent Networks with Attributed Random Walks☆28Updated 2 years ago
- AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning☆59Updated 6 years ago
- Deep Graph Kernels☆13Updated 9 years ago
- code for the paper in NeurIPS 2019☆40Updated 2 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆37Updated 4 years ago
- Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)☆31Updated 2 years ago
- Large-Scale Heterogeneous Feature Embedding☆15Updated 3 years ago
- The code repository for Discovering Conflicting Groups in Signed Networks (NeurIPS 2020)☆15Updated 3 years ago
- ☆16Updated 5 years ago
- PyTorch Implementation of GraphTSNE, ICLR’19☆135Updated 6 years ago
- The implementation of our AAAI 2020 paper "GSSNN: Graph Smoothing Splines Neural Network".☆20Updated 4 years ago
- This is a sample implementation of "TIMERS: Error-Bounded SVD Restart on Dynamic Networks"(AAAI 2018).☆12Updated 7 years ago
- The source code of the paper "Understanding Graph Neural Networks from Graph Signal Denoising Perspectives"☆22Updated 5 years ago
- The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical…☆51Updated 2 years ago
- A convolutional neural network for graph classification in PyTorch☆91Updated 6 years ago
- Implementation of "Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure".☆24Updated 5 years ago
- This repository summarises the open source codes of our group☆27Updated 2 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 5 years ago
- Code for "M. Zhang, Z. Cui, S. Jiang, and Y. Chen, Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space, AAAI-2018".☆21Updated 7 years ago
- ☆35Updated 6 years ago
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Implementation of Meta-GNN in TensorFlow☆47Updated 4 years ago
- Continuous-Time Relationship Prediction in Dynamic Heterogeneous Information Networks (TKDD 2019)☆18Updated 3 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆52Updated 5 years ago
- Unsupervised Network Embeddings for Graph Visualization, Clustering and Classification☆17Updated 5 years ago
- Software relating to relational empirical risk minimization☆17Updated 4 years ago
- A Python implementation of a fast approximation of the Weisfeiler-Lehman Graph Kernels.☆24Updated 6 years ago
- Reference implementation of the HEAT algorithm described in https://link.springer.com/chapter/10.1007/978-3-030-62362-3_4☆11Updated 2 years ago