[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
☆175Feb 19, 2024Updated 2 years ago
Alternatives and similar repositories for GSAT
Users that are interested in GSAT are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆123Aug 28, 2023Updated 2 years ago
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆25Jul 18, 2023Updated 2 years ago
- ☆58Sep 28, 2022Updated 3 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆209Feb 21, 2025Updated last year
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆138Nov 29, 2022Updated 3 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.
- Parameterized Explainer for Graph Neural Network☆145Feb 23, 2024Updated 2 years ago
- Papers about explainability of GNNs☆802Updated this week
- ☆16Sep 10, 2023Updated 2 years ago
- [ICML 2024] How Interpretable Are Interpretable Graph Neural Networks?☆16Jun 27, 2024Updated last year
- [VLDB'22] SUREL is a novel walk-based computation framework for efficient subgraph-based graph representation learning.☆20Apr 10, 2025Updated last year
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆93Dec 2, 2021Updated 4 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆46Mar 2, 2023Updated 3 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆22Jun 20, 2023Updated 2 years ago
- Papers about out-of-distribution generalization on graphs.☆169Jun 5, 2023Updated 2 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.
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆134Jul 15, 2023Updated 2 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆96Nov 16, 2023Updated 2 years ago
- Code for GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts☆16Dec 28, 2024Updated last year
- [Preprint] Graph State Space Convolution (GSSC)☆14Jun 11, 2024Updated last year
- Official repository for the paper: "Trees with Attention for Set Prediction Tasks" (ICML21)☆10Jan 19, 2022Updated 4 years ago
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆14Jun 15, 2024Updated last year
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆69Feb 16, 2025Updated last year
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆84Jul 27, 2023Updated 2 years ago
- [NeurIPS 2023] "Combating Bilateral Edge Noise for Robust Link Prediction"☆11Nov 3, 2023Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- graph neural networks, information theory, AI for Sciences☆23Apr 6, 2022Updated 4 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆38May 6, 2022Updated 4 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Jun 3, 2022Updated 3 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆70Nov 29, 2023Updated 2 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆34Dec 21, 2021Updated 4 years ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆54Apr 12, 2024Updated 2 years ago
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆209May 22, 2024Updated last year
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Nov 27, 2023Updated 2 years ago
- Pytorch implementation of WWW'23:"Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs"☆16Jul 2, 2023Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- A list of Graph Causal Learning materials.☆212Jan 24, 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
- ☆12Jul 17, 2023Updated 2 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆50Apr 8, 2024Updated 2 years ago
- The open source code for ICDM2022 paper "Unifying Graph Contrastive Learning with Flexible Contextual Scopes"☆21Oct 3, 2022Updated 3 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆67Jan 31, 2026Updated 3 months ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆83Dec 10, 2021Updated 4 years ago