Hongyang Gao 个人学术档案 - 学术资源搜索

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引用	3234	3200
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Shuiwang Ji, Professor and Presidenti...Department of Computer Science & Engineering, Texas A&M University在 tamu.edu 的电子邮件经过验证
Zhengyang WangApplied Scientist, Amazon.com在 amazon.com 的电子邮件经过验证
Lei CaiSenior Applied Scientist, Microsoft在 microsoft.com 的电子邮件经过验证
Meng LiuResearch Scientist, NVIDIA在 nvidia.com 的电子邮件经过验证
Zhaoning YuPhD student, Iowa State University在 iastate.edu 的电子邮件经过验证
Hao YuanResearch Scientist, Meta Platforms, Inc.在 fb.com 的电子邮件经过验证
Tianxiang Gao (高天翔)Department of Computer Science, Iowa State University在 iastate.edu 的电子邮件经过验证
Yongjun ChenApple在 apple.com 的电子邮件经过验证
Yi LiuAssistant Professor at Stony Brook University在 stonybrook.edu 的电子邮件经过验证
Hailiang LiuIowa State University在 iastate.edu 的电子邮件经过验证
Hridesh RajanProfessor and Chair, Iowa State University在 acm.org 的电子邮件经过验证
Wei LeAssociate Professor of Computer Science, Iowa State University在 iastate.edu 的电子邮件经过验证
Benjamin SteenhoekPhD Student, Iowa State University在 iastate.edu 的电子邮件经过验证
Jia (Kevin) LiuAssociate Professor of Electrical and Computer Engineering, The Ohio State University在 ece.osu.edu 的电子邮件经过验证
Chun YuanGraduate School at Shenzhen, Tsinghua University在 sz.tsinghua.edu.cn 的电子邮件经过验证
Yaochen XieApplied Scientist, Amazon在 amazon.com 的电子邮件经过验证
Xiaokai HuoIowa State Univeristy在 kaust.edu.sa 的电子邮件经过验证
Ke Zhang清华大学博士在 mails.tsinghua.edu.cn 的电子邮件经过验证
Yiming ZhuTsinghua University在 mails.tsinghua.edu.cn 的电子邮件经过验证
Siyuan SunPh.D student of Computer science Iowa State University在 iastate.edu 的电子邮件经过验证

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Hongyang Gao

Assistant Professor, Department of Computer Science, Iowa State University

在 iastate.edu 的电子邮件经过验证 - 首页

Deep Learning Graph Neural Networks


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Graph U-Nets H Gao, S Ji Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019	1238	2019
Large-Scale Learnable Graph Convolutional Networks H Gao, Z Wang, S Ji Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	644	2018
Towards deeper graph neural networks M Liu, H Gao, S Ji Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020	544	2020
Pixel Transposed Convolutional Networks H Gao, H Yuan, Z Wang, S Ji IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019	162*	2019
Deep adversarial learning for multi-modality missing data completion L Cai, Z Wang, H Gao, D Shen, S Ji Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	135	2018
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions H Gao, Z Wang, L Cai, S Ji IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020	92	2020
Topology-aware graph pooling networks H Gao, Y Liu, S Ji IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (12), 4512 …, 2021	81	2021
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation L Cai, H Gao, S Ji The SIAM International Conference on Data Mining (SDM), 2019	80	2019
Graph Representation Learning via Hard and Channel-Wise Attention Networks H Gao, S Ji Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019	65	2019
Learning graph pooling and hybrid convolutional operations for text representations H Gao, Y Chen, S Ji The world wide web conference, 2743-2749, 2019	42	2019
Molecular representation learning via heterogeneous motif graph neural networks Z Yu, H Gao International Conference on Machine Learning, 25581-25594, 2022	41*	2022
A global convergence theory for deep relu implicit networks via over-parameterization T Gao, H Liu, J Liu, H Rajan, H Gao arXiv preprint arXiv:2110.05645, 2021	16	2021
Voxel Deconvolutional Networks for 3D Brain Image Labeling Y Chen, H Gao, L Cai, M Shi, D Shen, S Ji Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	16	2018
Efficient and Invariant Convolutional Neural Networks for Dense Prediction H Gao, S Ji IEEE International Conference on Data Mining (ICDM), 2017	16	2017
Motifexplainer: a motif-based graph neural network explainer Z Yu, H Gao arXiv preprint arXiv:2202.00519, 2022	13	2022
Kronecker attention networks H Gao, Z Wang, S Ji Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020	13	2020
Adaptive Convolutional ReLUs H Gao, L Cai, S Ji Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 3914-3921, 2020	11	2020
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection B Steenhoek, H Gao, W Le Proceedings of the 46th IEEE/ACM International Conference on Software …, 2024	5	2024
A mathematical view of attention models in deep learning S Ji, Y Xie, H Gao Texas A&M University, April, 2019	4	2019
Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning S Sun, H Gao Advances in Neural Information Processing Systems 36, 2024	3	2024

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