AnoushkaVyas / GraphZooLinks
Facilitating learning, using, and designing graph processing pipelines/models systematically.
☆26Updated 3 years ago
Alternatives and similar repositories for GraphZoo
Users that are interested in GraphZoo are comparing it to the libraries listed below
Sorting:
- Source code for From Stars to Subgraphs (ICLR 2022)☆71Updated last year
- GNNExplainer implementation using DGL☆31Updated 4 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆70Updated 10 months ago
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆103Updated 4 years ago
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆104Updated 2 years ago
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆59Updated 4 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆116Updated last year
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆84Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆92Updated 2 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆83Updated 2 years ago
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆99Updated last year
- ☆62Updated 3 years ago
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆54Updated 3 years ago
- ☆77Updated 3 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆48Updated last year
- Collection of papers relating data-driven higher-order graph/networks researches.☆73Updated 3 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆172Updated last year
- ☆57Updated 4 years ago
- CIKM 2021: Pooling Architecture Search for Graph Classification☆21Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 6 months ago
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆80Updated 4 years ago
- The pytorch implementation of ClusterSCL (WWW2022).☆15Updated 2 years ago
- Schedule for learning on graphs seminar☆109Updated 2 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆126Updated last year
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆203Updated 9 months ago
- Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"☆35Updated 3 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆71Updated 3 years ago
- ☆19Updated 2 years ago
- Dynamic Graph Benchmark☆87Updated 2 years ago
- Parameterized Explainer for Graph Neural Network☆140Updated last year