Quan Gan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
33
Venues
23
Active years
2005–2025
Best venue rank
A*
Where they publish
- A*ICML4 papers
- A*KDD3 papers
- CIGARSS2 papers
- A*VLDB2 papers
- A*WWW2 papers
- A*ICLR2 papers
- NationalGRC2 papers
- AAISTATS1 paper
- BIJCNN1 paper
- ACIKM1 paper
- CISPA1 paper
- BTrustCom1 paper
- A*SIGIR1 paper
- AWSDM1 paper
- ASC1 paper
- A*AAAI1 paper
- BAINA1 paper
- A*ICCV1 paper
- A*CVPR1 paper
- BACII1 paper
- NationalISKE1 paper
- CISNN1 paper
- BSMC1 paper
Papers
33 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners. | Yuxin Wang, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang, Xipeng Qiu |
| 2025 | ICML | Griffin: Towards a Graph-Centric Relational Database Foundation Model. | Yanbo Wang, Xiyuan Wang, Quan Gan, Minjie Wang, Qibin Yang, David Wipf, Muhan Zhang |
| 2025 | IJCNN | Enhance the prior knowledge in Bayesian learning with semantic similarity for few-shot image classification. | Jingyu Chen, Jiaying Wu, Can Gao, Zheng Huang, Zhaoman Zhong, Quan Gan |
| 2024 | CIKM | ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction. | Yanlin Zhang, Ning Li, Quan Gan, Weinan Zhang, David Wipf, Minjie Wang |
| 2024 | IGARSS | A Transformer-Based Cross-Resolution Target Recognition Method for SAR Images Based on Feature Alignment and Aggregation. | Kailing Tang, Zongyong Cui, Zheng Zhou, Quan Gan, Zongjie Cao |
| 2024 | IGARSS | Class-Incremental SAR Obeject Detection Via Adaptive Distributed Response Distillation. | Jingyu Li, Zongjie Cao, Quan Gan, Yu Tian, Zongyong Cui |
| 2024 | ISPA | A Multipath Satellite Routing to Enhance Networking Performance for LEO Constellations. | Chenqiang Tong, Chen Chen, Wei Han, Zhiyi Wang, Lixin Lan, Chengbin Huang, Fan Jin, Quan Gan, Shaohua Wan |
| 2024 | KDD | Graph Machine Learning Meets Multi-Table Relational Data. | Quan Gan, Minjie Wang, David Wipf, Christos Faloutsos |
| 2024 | TrustCom | Towards a Robust Medical Record System: Integrating Logical Reasoning for Trustworthy Data Management. | Hanning Zhang, Guansheng Wang, Junwei Feng, Lei Feng, Quan Gan, Long Ji |
| 2024 | VLDB | GFS: Graph-based Feature Synthesis for Prediction over Relational Databases. | Han Zhang, Quan Gan, David Wipf, Weinan Zhang |
| 2024 | VLDB | 4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. | Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang |
| 2023 | ICML | From Hypergraph Energy Functions to Hypergraph Neural Networks. | Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf |
| 2023 | KDD | Dense Representation Learning and Retrieval for Tabular Data Prediction. | Lei Zheng, Ning Li, Xianyu Chen, Quan Gan, Weinan Zhang |
| 2023 | WWW | Tutorials at The Web Conference 2023. | Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espn-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Kk-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu |
| 2022 | ICLR | Inductive Relation Prediction Using Analogy Subgraph Embeddings. | Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan |
| 2022 | ICLR | Why Propagate Alone? Parallel Use of Labels and Features on Graphs. | Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf |
| 2022 | ICML | GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. | Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu |
| 2022 | SIGIR | Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. | Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi |
| 2021 | ICML | Graph Neural Networks Inspired by Classical Iterative Algorithms. | Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf |
| 2021 | WSDM | Scalable Graph Neural Networks with Deep Graph Library. | Da Zheng, Minjie Wang, Quan Gan, Xiang Song, Zheng Zhang, George Karypis |
| 2020 | KDD | Scalable Graph Neural Networks with Deep Graph Library. | Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis |
| 2020 | WWW | Learning Graph Neural Networks with Deep Graph Library. | Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis |
| 2020 | SC | DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. | Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis |
| 2017 | AAAI | Differentiating Between Posed and Spontaneous Expressions with Latent Regression Bayesian Network. | Quan Gan, Siqi Nie, Shangfei Wang, Qiang Ji |
| 2017 | AINA | The Performance Impact of Buffer Sizes for Multi-path TCP in Internet Setups. | Feng Zhou, Thomas Dreibholz, Xing Zhou, Fa Fu, Yuyin Tan, Quan Gan |
| 2017 | ICCV | A Multimodal Deep Regression Bayesian Network for Affective Video Content Analyses. | Quan Gan, Shangfei Wang, Longfei Hao, Qiang Ji |
| 2016 | CVPR | Facial Expression Intensity Estimation Using Ordinal Information. | Rui Zhao, Quan Gan, Shangfei Wang, Qiang Ji |
| 2015 | ACII | Posed and spontaneous facial expression differentiation using deep Boltzmann machines. | Quan Gan, Chongliang Wu, Shangfei Wang, Qiang Ji |
| 2010 | ISKE | Artificial neural network model to predict compositional viscosity over a broad range of temperatures. | Yiqing Miao, Quan Gan, David W. Rooney |
| 2007 | ISNN | A Fuzzy Neural Network Based on Back-Propagation. | Jin Huang, Quan Gan, Linhui Cai |
| 2006 | GRC | A self-learning model based on granular computing. | Quan Gan, Guoyin Wang, Jun Hu |
| 2005 | GRC | A rule generation algorithm based on granular computing. | Jiu-Jiang An, Guoyin Wang, Yu Wu, Quan Gan |
| 2005 | SMC | Humanoids for lunar and planetary surface operations. | Adrian Stoica, Didier Keymeulen, Ambrus Csaszar, Quan Gan, Timothy Hidalgo, Jeff Moore, Jason Newton, Steven Sandoval, Jiajing Xu |