vijaydwivedi75 / gnn-lspeLinks
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
☆257Updated 3 years ago
Alternatives and similar repositories for gnn-lspe
Users that are interested in gnn-lspe are comparing it to the libraries listed below
Sorting:
- ☆156Updated 3 years ago
- Official Pytorch code for Structure-Aware Transformer.☆258Updated 2 years ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆157Updated last year
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆349Updated 2 years ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆193Updated last year
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 3 years ago
- Representing Long-Range Context for Graph Neural Networks with Global Attention☆131Updated 3 years ago
- The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…☆306Updated last year
- [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)☆329Updated last year
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆272Updated 2 years ago
- ☆135Updated last year
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆123Updated 5 months ago
- A graph transformer framework☆77Updated 2 years ago
- Implementation of Directional Graph Networks in PyTorch and DGL☆118Updated 4 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated 3 years ago
- Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddin…☆227Updated last year
- Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"☆210Updated last year
- Code for our paper "Attending to Graph Transformers"☆87Updated last year
- Subgraph Neural Networks (NeurIPS 2020)☆198Updated 4 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 2 years ago
- [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)☆104Updated last year
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆196Updated 3 months ago
- Official Pytorch Implementation of GraphiT☆109Updated 3 years ago
- A list for GNNs and related works.☆93Updated 3 weeks ago
- Edge-Augmented Graph Transformer☆77Updated last year
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆115Updated 2 months ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆70Updated last year
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆89Updated 2 years ago
- Transformer-based Spectral Graph Neural Networks☆82Updated 7 months ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆43Updated 2 years ago