ventr1c / RES-GCLLinks
An official PyTorch implementation of "Certifiably Robust Graph Contrastive Learning" (NeurIPS 2023)
☆11Updated last year
Alternatives and similar repositories for RES-GCL
Users that are interested in RES-GCL are comparing it to the libraries listed below
Sorting:
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆27Updated 3 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Updated last year
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated 2 years ago
- [ICML2024] "LLaGA: Large Language and Graph Assistant", Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang☆134Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆44Updated 2 years ago
- Official implementation of GOAT model (ICML2023)☆38Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆61Updated 2 years ago
- ☆18Updated 3 years ago
- [ICLR 2023 Oral] Towards Open Temporal Graph Neural Networks☆33Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Updated 2 years ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆47Updated 10 months ago
- A curated list of resources for OOD detection with graph data.☆19Updated last year
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆82Updated 2 years ago
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆19Updated 4 years ago
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆40Updated 11 months ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- Official Repo of SimTeG☆42Updated last year
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆116Updated 2 years ago
- GFT: Graph Foundation Model with Transferable Tree Vocabulary, NeurIPS 2024.☆52Updated 5 months ago
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆28Updated last year
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆32Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated 2 years ago
- Label-free Node Classification on Graphs with Large Language Models (LLMS)☆85Updated last year
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated 2 years ago
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago
- An Open and Unified Benchmark for Graph Condensation (submitted to NeurIPS 2024 Datasets and Benchmarks Track)☆19Updated last year
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Updated 11 months ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆24Updated 2 years ago
- ☆59Updated 11 months ago