Radical3-HeZhang / Awesome-Trustworthy-GNNsLinks
☆98Updated 11 months ago
Alternatives and similar repositories for Awesome-Trustworthy-GNNs
Users that are interested in Awesome-Trustworthy-GNNs are comparing it to the libraries listed below
Sorting:
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆85Updated 8 months ago
- Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"☆89Updated 4 years ago
- ☆24Updated 3 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆136Updated 2 years ago
- Schedule for learning on graphs seminar☆109Updated 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
- How Powerful are Spectral Graph Neural Networks☆72Updated last year
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆89Updated 2 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆80Updated 4 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆88Updated 3 years ago
- Parameterized Explainer for Graph Neural Network☆134Updated last year
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆95Updated last year
- DGL implementation of GRAND(Graph Random Neural Network, NeurIPS 2020)☆18Updated 4 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆114Updated last year
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated last week
- Code for paper https://arxiv.org/abs/2102.13186☆44Updated 4 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆92Updated 8 months ago
- Papers about out-of-distribution generalization on graphs.☆166Updated 2 years ago
- Pairwise learning neural link prediction for ogb link prediction☆41Updated 3 years ago
- Code for Neurips2021 Paper "Topology-Imbalance Learning for Semi-Supervised Node Classification".☆54Updated 3 years ago
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago
- ☆76Updated 3 years ago
- ☆97Updated 4 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆138Updated 7 months ago
- TNNLS: A Synergistic Approach for Graph Anomaly Detection with Pattern Mining and Feature Learning; CIKM'20: Error-bounded Graph Anomaly …☆42Updated last year
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 2 years ago
- A collection of graph data used for semi-supervised node classification.☆40Updated 2 years ago
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 3 years ago