☆16Sep 10, 2023Updated 2 years ago
Alternatives and similar repositories for AAGOD
Users that are interested in AAGOD are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A curated list of resources for OOD detection with graph data.☆19Dec 30, 2023Updated 2 years ago
- [NeurIPS 2023] "Combating Bilateral Edge Noise for Robust Link Prediction"☆11Nov 3, 2023Updated 2 years ago
- [NeurIPS 2023] Combating Bilateral Edge Noise for Robust Link Prediction☆13Nov 3, 2023Updated 2 years ago
- GOODAT: Towards Test-time Graph Out-of-Distribution Detection☆12Mar 18, 2024Updated 2 years ago
- ☆10Jun 11, 2023Updated 3 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆211Feb 21, 2025Updated last year
- The paper "Deep Graph Level Anomaly Detection with Contrastive Learning" has been accepted by Scientific Reports Journal.☆11Feb 10, 2023Updated 3 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆45Mar 2, 2023Updated 3 years ago
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆84Jul 27, 2023Updated 3 years ago
- Code for "Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing"☆15Oct 1, 2023Updated 2 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆35Feb 20, 2020Updated 6 years ago
- source code of AAAI 2024 paper "Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization".☆18Apr 29, 2024Updated 2 years ago
- Official Implementation of Expressivity and Generalization: Fragment-Biases for Molecular GNNs☆20Nov 6, 2024Updated last year
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆175Feb 19, 2024Updated 2 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Official implementation for GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs (NeurIPS 20…☆20Oct 14, 2022Updated 3 years ago
- Dataset Pinocchio for paper "Towards Understanding Factual Knowledge of Large Language Models" accepted by ICLR 2024 (Spotlight)☆12Mar 13, 2024Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆43Jun 15, 2023Updated 3 years ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆16Nov 6, 2023Updated 2 years ago
- The source code of the experimental evaluation of Deprez et al. (nd)☆11Oct 8, 2025Updated 10 months ago
- Certifiable Robustness to Graph Perturbations☆14May 8, 2020Updated 6 years ago
- Size-Invariant Graph Representations for Graph Classification Extrapolations (ICML 2021 Long Talk)☆22Jan 26, 2023Updated 3 years ago
- Official implementation of paper "GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfe…☆18Jan 27, 2024Updated 2 years ago
- Variational autoencoder in Keras on MNIST images☆11Dec 3, 2018Updated 7 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- This is the implementation of OODGAT from KDD'22: Learning on Graphs with Out-of-Distribution Nodes.☆23Sep 2, 2022Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆123Aug 28, 2023Updated 2 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Nov 4, 2024Updated last year
- a robust metric (robust fidelity) for XGNN (ICLR24)☆12Jun 3, 2025Updated last year
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆23Aug 25, 2024Updated last year
- This repository contains the code to reproduce experiments presented in the paper "Path Neural Networks: Expressive and Accurate Graph Ne…☆27Jun 28, 2023Updated 3 years ago
- ☆20Sep 16, 2025Updated 10 months ago
- Can We Predict Before Executing Machine Learning Agents?☆21Jul 7, 2026Updated last month
- ☆16Aug 14, 2019Updated 6 years ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- [NeurIPS'23] Towards Self-Interpretable Graph-Level Anomaly Detection☆30Jul 18, 2024Updated 2 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆69Feb 16, 2025Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆26Oct 16, 2023Updated 2 years ago
- Code for our ACL 2023 paper: Causality-aware Concept Extraction based on Knowledge-guided Prompting☆14Aug 19, 2023Updated 2 years ago
- StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs☆26Oct 22, 2023Updated 2 years ago
- ☆21Aug 3, 2021Updated 5 years ago
- 用于学习“从零开始重写sylar C++高性能分布式服务器框架“，添加了很多注解和文档方便学习☆12Feb 28, 2024Updated 2 years ago