LechengKong / MAG-GNNLinks
Official implementation of MAG-GNN: an RL-boosted graph learning framework.
☆19Updated last year
Alternatives and similar repositories for MAG-GNN
Users that are interested in MAG-GNN are comparing it to the libraries listed below
Sorting:
- Implementation of the SPN model and the experiments from the LoG 2022 paper "Shortest Path Networks for Graph Property Prediction".☆25Updated 2 years ago
- A curated list of graph reinforcement learning papers.☆72Updated 3 years ago
- Accurate Node Feature Estimation with Structured Variational Graph Autoencoder (KDD 2022)☆18Updated 2 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated last year
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆44Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆88Updated last year
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 3 years ago
- Official implementation of the ICML 2022 paper "Going Deeper into Permutation-Sensitive Graph Neural Networks"☆27Updated 3 years ago
- ☆14Updated 2 years ago
- ☆14Updated last year
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆59Updated 2 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆70Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- ☆13Updated 4 years ago
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆82Updated last year
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- Unified Graph Transformer (UGT) is a novel Graph Transformer model specialised in preserving both local and global graph structures and d…☆27Updated 3 months ago
- Code for our paper "Attending to Graph Transformers"☆89Updated last year
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆46Updated 11 months ago
- ☆57Updated 3 years ago
- ☆12Updated 5 months ago
- CIKM 2021: Pooling Architecture Search for Graph Classification☆20Updated 2 years ago
- ☆20Updated 4 years ago
- [VLDB'23] SUREL+ is a novel set-based computation framework for scalable subgraph-based graph representation learning.☆17Updated 3 months ago
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆64Updated last year
- Edge-Augmented Graph Transformer☆77Updated last year
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆54Updated 2 years ago
- Implementation of ICML'24 Paper "Less is More: on the Over-Globalizing Problem in Graph Transformers"☆45Updated last year
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆81Updated 2 years ago