facebookresearch / shaDow_GNNLinks
[NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architectures
☆137Updated 3 years ago
Alternatives and similar repositories for shaDow_GNN
Users that are interested in shaDow_GNN are comparing it to the libraries listed below
Sorting:
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆165Updated 3 years ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆195Updated last year
- SIGN: Scalable Inception Graph Network☆95Updated 4 years ago
- Distance Encoding for GNN Design☆187Updated 4 years ago
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆210Updated 2 years ago
- PPRGo model in PyTorch, as proposed in "Scaling Graph Neural Networks with Approximate PageRank" (KDD 2020)☆126Updated 3 years ago
- [ICLR 2021] Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (https://arxiv.org/abs/2010.13993)☆292Updated 4 years ago
- ☆138Updated 2 years ago
- ☆155Updated 4 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆116Updated 3 years ago
- Papers about developing deep Graph Neural Networks (GNNs)☆298Updated 2 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆94Updated last year
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 4 months ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆273Updated 2 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆117Updated 5 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- An open-source implementation of SEAL for link prediction in open graph benchmark (OGB) datasets.☆239Updated 2 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆97Updated 3 years ago
- Official implementation of our FLAG paper (CVPR2022)☆145Updated 3 years ago
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆125Updated 3 years ago
- Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" …☆323Updated last year
- ☆302Updated 3 years ago
- Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"☆76Updated 2 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆232Updated 2 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆199Updated last year
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆142Updated 2 weeks ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆82Updated 2 years ago
- Official implementation of our VQ-GNN paper (NeurIPS2021)☆38Updated 3 years ago
- [ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision☆159Updated 2 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 3 years ago