├── README.md └── LICENSE /README.md: -------------------------------------------------------------------------------- 1 | # awesome-hypergraph-learning 2 | A curated list of awesome Hypergraph Learning frameworks, libraries and software. 3 | [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome) 4 | 5 | ## Contents 6 | 7 | ## Table of Contents 8 | 9 | * **[Surveys](#surveys)** 10 | 11 | * **[Papers](#papers)** 12 | 13 | * **[Datasets](#datasets)** 14 | 15 | * **[Frameworks](#frameworks)** 16 | 17 | 18 | 19 | ## Surveys 20 | 21 | * **Hypergraph Learning: Methods and Practices** *Yue Gao, Zizhao Zhang, Haojie Lin, Xibin Zhao, Shaoyi Du, Changqing Zou* 22 | [paper](https://pubmed.ncbi.nlm.nih.gov/33211654/) 23 | * **Higher order learning with graphs** *Sameer Agarwal, 24 | Kristin Branson,Serge Belongie* 25 | [paper](https://homes.cs.washington.edu/~sagarwal/holg.pdf) 26 | ## Papers 27 | 28 | #### Architectures 29 | * **Sheaf Hypergraph Networks** [paper](https://arxiv.org/pdf/2304.09097.pdf) 30 | * **Learning with Hypergraphs: Clustering, Classification, and Embedding.** [paper](https://proceedings.neurips.cc/paper/2006/file/dff8e9c2ac33381546d96deea9922999-Paper.pdf) 31 | * **You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.** [paper](https://openreview.net/forum?id=hpBTIv2uy_E) | [code](https://github.com/jianhao2016/AllSet) 32 | * **HyperGCN: A New Method of Training Graph 33 | Convolutional Networks on Hypergraphs** [paper](https://proceedings.neurips.cc/paper/2019/file/1efa39bcaec6f3900149160693694536-Paper.pdf) | [code](https://github.com/malllabiisc/HyperGCN) 34 | * **Hypergraph Neural Networks** [paper](https://arxiv.org/pdf/1809.09401.pdf) | [code](https://github.com/iMoonLab/HGNN) 35 | * **Hypergraph Convolution and Hypergraph Attention** [paper](https://arxiv.org/pdf/1901.08150.pdf) | [code](https://pytorch-geometric.readthedocs.io/en/latest/_modules/torch_geometric/nn/conv/hypergraph_conv.html) 36 | * **Hyper-SAGNN: a self-attention based graph neural network for hypergraphs** [paper](https://openreview.net/forum?id=ryeHuJBtPH) 37 | * **Hypergraph Attention Networks** [paper](https://ieeexplore.ieee.org/document/9342986) 38 | * **HNHN: Hypergraph Networks with Hyperedge Neurons** 39 | [paper](https://arxiv.org/pdf/2006.12278v1.pdf) | [code](https://github.com/twistedcubic/HNHN) 40 | * **Hypergraph Learning with Line Expansion** [paper](https://arxiv.org/pdf/2005.04843.pdf) 41 | * **Hypergraph Attention Isomorphism Network by Learning Line Graph Expansion** [paper](https://ieeexplore.ieee.org/document/9378335) | [code](https://github.com/kdmsit/HAIN) 42 | * **Be More with Less: Hypergraph Attention Networks for 43 | Inductive Text Classification** [paper](https://aclanthology.org/2020.emnlp-main.399.pdf) 44 | * **HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs** [paper](https://openreview.net/forum?id=cKnKJcTPRcV) 45 | * **Deep Hyperedges: a Framework for Transductive and Inductive Learning on Hypergraphs** [paper](https://arxiv.org/pdf/1910.02633v1.pdf) | [code](https://github.com/0xpayne/deep-hyperedges) 46 | * **Edge Representation Learning with Hypergraphs** [paper](https://arxiv.org/pdf/2106.15845v2.pdf) | [code](https://github.com/harryjo97/EHGNN) 47 | 48 | * **DHGNN: Dynamic Hypergraph Neural Networks** [paper](https://www.ijcai.org/proceedings/2019/0366.pdf) | [code](https://github.com/iMoonLab/DHGNN) 49 | #### Recommender systems 50 | * **Hypergraph Contrastive Collaborative Filtering** [paper](https://arxiv.org/pdf/2204.12200v2.pdf) | [code](https://github.com/akaxlh/hccf) 51 | * **Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation** [paper](https://arxiv.org/pdf/2012.06852v5.pdf) | [code](https://github.com/xiaxin1998/DHCN) 52 | * **Hyperbolic Hypergraphs for Sequential Recommendation** [paper](https://arxiv.org/pdf/2108.08134.pdf) 53 | #### Knowledge systems 54 | * **Knowledge Hypergraphs: Prediction Beyond Binary Relations** [paper](https://www.ijcai.org/proceedings/2020/0303.pdf) 55 | #### Computer Vision 56 | * **Adaptive Hypergraph Learning and its Application in Image Classification** [paper](https://ieeexplore.ieee.org/document/6165360) 57 | * **Inductive Multi-Hypergraph Learning and Its Application on View-Based 3D Object Classification** [paper](https://ieeexplore.ieee.org/document/8424480) 58 | 59 | 60 | ## Datasets 61 | * **Collection of datasets from Austin R. Benson' research projects.** [website](https://www.cs.cornell.edu/~arb/data/) 62 | 63 | ## Frameworks 64 | * [HyperNetX](https://github.com/pnnl/HyperNetX) is a Python preliminary library that generalizes traditional graph metrics to hypergraphs, and it provides proper documentation and tutorials. 65 | * [multihypergraph](github.com/vaibhavkarve/multihypergraph) A simple python package for graph theory that supports multi-edges, hyper-edges, looped-edges and every other combination of these. 66 | 67 | 68 | 69 | **License** 70 | - [CC0 Universal](https://github.com/giuliacassara/awesome-hypergraph-learning/blob/master/LICENSE) 71 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Creative Commons Legal Code 2 | 3 | CC0 1.0 Universal 4 | 5 | CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE 6 | LEGAL SERVICES. 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