├── LICENSE └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2020 shiruipan 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # graph-deep-learning 2 | This page summarises the open source code of our group, mostly on graph learning & deep learning. More source code will be released as it is ready for publishing. You can visit your [GRAND Lab page on Github](https://github.com/GRAND-Lab) for more details. 3 | 4 | ## Graph Learning & Deep Learning 5 | 6 | - **Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination (NeurIPS 2022)** 7 | - Yizhen Zheng, Shirui Pan, Vincent Lee, Yu Zheng, Philip S. Yu 8 | - [[Paper]](https://shiruipan.github.io/publication/neurips-22-zheng/) 9 | - [[Python Implementation]](https://github.com/zyzisastudyreallyhardguy/Graph-Group-Discrimination) 10 | 11 | - **Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs (NeurIPS 2022)** 12 | - Ming Jin, Yuan-Fang Li, Shirui Pan 13 | - [[Paper]](https://mingjin.dev/assets/pdf/neurips-22-jin.pdf) 14 | - [[Python Implementation]](https://github.com/KimMeen/Neural-Temporal-Walks) 15 | 16 | - **Unifying Graph Contrastive Learning with Flexible Contextual Scopes (ICDM 2022)** 17 | - Yizhen Zheng, Yu Zheng, Xiaofei Zhou, Chen Gong, Vincent CS Lee, Shirui Pan 18 | - [[Paper]](https://arxiv.org/abs/2210.08792) 19 | - [[Python Implementation]](https://github.com/zyzisastudyreallyhardguy/UGCL) 20 | 21 | - **Towards Unsupervised Deep Graph Structure Learning (WWW 2022)** 22 | - Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan 23 | - [[Paper]](https://arxiv.org/abs/2201.06367) 24 | - [[Python Implementation]](https://github.com/GRAND-Lab/SUBLIME) 25 | 26 | - **Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering (TKDE 2022)** 27 | - Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang 28 | - [[Paper]](https://arxiv.org/abs/2107.04755) 29 | - [[Python Implementation]](https://github.com/nnzhan/AutoGCN) 30 | 31 | - **Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning (IJCAI 2021)** 32 | - Ming Jin, Yizhen Zheng, Yuan-Fang Li, Chen Gong, Chuan Zhou, Shirui Pan 33 | - [[Paper]](https://shiruipan.github.io/publication/ijcai-2021-jin/) 34 | - [[Python Implementation]](https://github.com/GRAND-Lab/MERIT) 35 | 36 | - **Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning 37 | (AAAI 2021)** 38 | - Sheng Wan, Shirui Pan, Jian Yang, Chen Gong 39 | - [[Paper]](https://shiruipan.github.io/publication/aaai-2021-wan/) 40 | - [[Python Implementation]](https://github.com/LEAP-WS/CG3) 41 | 42 | - **ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning (CIKM 2021)** 43 | - Ming Jin, Yixin Liu, Yu Zheng, Lianhua Chi, Yuan-Fang Li, Shirui Pan 44 | - [[Paper]](https://shiruipan.github.io/publication/cikm-21-jin/) 45 | - [[Python Implementation]](https://github.com/GRAND-Lab/ANEMONE) 46 | 47 | - **Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (TNNLS 2021)** 48 | - Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis 49 | - [[Paper]](https://shiruipan.github.io/publication/tnnls-21-liu/) 50 | - [[Python Implementation]](https://github.com/GRAND-Lab/CoLA) 51 | 52 | - **Open-World Graph Learning (ICDM 2020)** 53 | - Man Wu, Shirui Pan, Xingquan Zhu 54 | - [[Paper]](https://shiruipan.github.io/publication/icdm-20-wu/) 55 | - [[Python Implementation]](https://github.com/mandy976/OpenWGL) 56 | 57 | - **One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting (TPAMI 2020)** 58 | - Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Chuan Zhou, Zongyuan Ge, Steven Su 59 | - [[Paper]](https://shiruipan.github.io/publication/tpami-20-zhang/) 60 | - [[Python Implementation]](https://github.com/MiaoZhang0525/NSAS_FOR_CVPR) 61 | 62 | - **Graph Stochastic Neural Networks for Semi-supervised Learning (NeurIPS 2020)** 63 | - Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, Jilong Wang 64 | - [[Paper]](https://shiruipan.github.io/publication/neurips-20-wang/) 65 | - [[Python Implementation]](https://github.com/GSNN/GSNN) 66 | 67 | - **Graph Geometry Interaction Learning (NeurIPS 2020)** 68 | - Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, Bin Wang 69 | - [[Paper]](https://shiruipan.github.io/publication/neurips-20-zhu/) 70 | - [[Python Implementation]](https://github.com/CheriseZhu/GIL) 71 | 72 | - **Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement (NeurIPS 2020)** 73 | - Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Zongyuan Ge, Steven Su 74 | - [[Paper]](https://shiruipan.github.io/publication/neurips-20-zhang/) 75 | - [[Python Implementation]](https://github.com/MiaoZhang0525/EENAS_for_NeurIPS2020) 76 | 77 | - **Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks (KDD 2020)** 78 | - Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang 79 | - [[Paper]](https://shiruipan.github.io/publication/kdd-2020-wu/) 80 | - [[Python Implementation]](https://github.com/nnzhan/MTGNN) 81 | 82 | - **Overcoming Multi-Model Forgetting in One-Shot NAS with Diversity Maximization (CVPR 2020)** 83 | - Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Steven Su 84 | - [[Paper]](https://shiruipan.github.io/publication/cvpr-2020-zhang/) 85 | - [[Python Implementation]](https://github.com/MiaoZhang0525/NSAS_FOR_CVPR) 86 | 87 | - **Unsupervised Domain Adaptive Graph Convolutional Networks (WWW 2020)** 88 | - Man Wu, Shirui Pan, Chuan Zhou, Xiaojun Chang, Xingquan Zhu 89 | - [[Paper]](https://shiruipan.github.io/publication/www-2020-wu/) 90 | - [[Python Implementation]](https://github.com/mandy976/UDAGCN) 91 | 92 | - **GSSNN: Graph Smoothing Splines Neural Network (AAAI 2020)** 93 | - Shichao Zhu, Lewei Zhou, Shirui Pan, Chuan Zhou, Guiying Yan, Bin Wang 94 | - [[Paper]](https://shiruipan.github.io/publication/aaai-2020-zhu) 95 | - [[Python Implementation]](https://github.com/CheriseZhu/GSSNN) 96 | 97 | 98 | - **Reinforcement Learning based Meta-path Discovery in Large-scale Heterogeneous Information Networks (AAAI 2020)** 99 | - Guojia Wan, Bo Du, Shirui Pan, Gholamreza Haffari 100 | - [[Paper]](https://shiruipan.github.io/publication/aaai-2020-wan/) 101 | - [[Python Implementation]](https://github.com/mxz12119/MPDRL) 102 | 103 | 104 | - **Relation Structure-Aware Heterogeneous Graph Neural Network (ICDM 2019)** 105 | - Shichao Zhu, Chuan Zhou, Shirui Pan, Xingquan Zhu, Bin Wang 106 | - [[Paper]](https://shiruipan.github.io/publication/icdm-19-zhu/) 107 | - [[Python Implementation]](https://github.com/CheriseZhu/RSHN) 108 | 109 | 110 | - **Graph WaveNet for Deep Spatial-Temporal Graph Modeling (IJCAI 2019)** 111 | - Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Chengqi Zhang 112 | - [[Paper]](https://shiruipan.github.io/publication/ijcai-2019-wu/) 113 | - [[Python Implementation]](https://github.com/nnzhan/Graph-WaveNet) 114 | 115 | 116 | - **Adversarially regularized graph autoencoder for graph embedding (IJCAI 2018)** 117 | - Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang 118 | - [[Paper]](https://shiruipan.github.io/publication/pan-adversarially-2018/) 119 | - [[Python Implementation]](https://github.com/Ruiqi-Hu/ARGA) 120 | 121 | - **Binarized attributed network embedding (ICDM 2018)** 122 | - Hong Yang, Shirui Pan, Peng Zhang, Ling Chen, Defu Lian, Chengqi Zhang 123 | - [[Paper]](https://shiruipan.github.io/publication/yang-binarized-2018/) 124 | - [[Matlab Implementation]](https://github.com/shiruipan/BANE) 125 | - [[Python Reference]](https://github.com/benedekrozemberczki/BANE) 126 | 127 | - **MGAE: marginalized graph autoencoder for graph clustering (CIKM 2017)** 128 | - Chun Wang, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang 129 | - [[Paper]](https://shiruipan.github.io/publication/wang-mgae-2017/) 130 | - [[Matlab Implementation]](https://github.com/FakeTibbers/MGAE) 131 | 132 | - **Tri-party deep network representation (IJCAI 2016)** 133 | - Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang 134 | - [[Paper]](https://shiruipan.github.io/publication/pan-tri-party-2016/) 135 | - [[Python Implementation]](https://github.com/shiruipan/TriDNR) 136 | 137 | 138 | 139 | 140 | 141 | 142 | 143 | 144 | 145 | 146 | 147 | 148 | --------------------------------------------------------------------------------