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2020 – today
- 2024
[j4]Zhiqian Chen
, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks. ACM Comput. Surv. 56(5): 126:1-126:42 (2024)- [j3]Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Citation Forecasting with Multi-Context Attention-Aided Dependency Modeling. ACM Trans. Knowl. Discov. Data 18(6): 144:1-144:23 (2024) - [c26]Bingshu Shi, Meiling Liu, Jiyun Zhou, Kaiqun Fu:
Sentiment Summarization Generation Based on Multi Instance Learning and Graph Convolution on Social Media. CSCWD 2024: 242-247 - [c25]Lin Guo, Meiling Liu, Kaiqun Fu, Jiyun Zhou:
SSIE-Diffusion: Personalized Generative Model for Subject-Specific Image Editing. IJCNN 2024: 1-8 - [i11]Bobby Azad, Pourya Adibfar, Kaiqun Fu:
TransDAE: Dual Attention Mechanism in a Hierarchical Transformer for Efficient Medical Image Segmentation. CoRR abs/2409.02018 (2024) - 2023
- [c24]Yangxiao Bai, Kaiqun Fu:
PanTop: Pandemic Topic Detection and Monitoring System (Student Abstract). AAAI 2023: 16158-16159 - [c23]Hoa Ta, Shi Wen Wong, Nathan McClanahan, Jung-Han Kimn, Kaiqun Fu:
Exploration on Physics-Informed Neural Networks on Partial Differential Equations (Student Abstract). AAAI 2023: 16344-16345 - [c22]Shengkun Wang, Yangxiao Bai, Kaiqun Fu, Linhan Wang, Chang-Tien Lu, Taoran Ji:
ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction. ASONAM 2023: 538-542 - [c21]Yanshen Sun, Kaiqun Fu, Chang-Tien Lu:
RoadFormer: Road-Anchored Adversarial Dynamic Graph Transformer for Unlimited-Range Traffic Incident Impact Prediction. IEEE Big Data 2023: 895-904 - [c20]Shengkun Wang, Yangxiao Bai, Taoran Ji, Kaiqun Fu, Linhan Wang, Chang-Tien Lu:
Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices. IEEE Big Data 2023: 1863-1872 - [i10]Yanshen Sun, Kaiqun Fu, Chang-Tien Lu:
DG-Trans: Dual-level Graph Transformer for Spatiotemporal Incident Impact Prediction on Traffic Networks. CoRR abs/2303.12238 (2023) - [i9]Deepthi Kolady, Amrit Dumre, Weiwei Zhang, Kaiqun Fu, Marcia O'Leary, Laura Rose:
Social media use among American Indians in South Dakota: Preferences and perceptions. CoRR abs/2307.01404 (2023) - [i8]Kaiqun Fu, Yangxiao Bai, Weiwei Zhang, Deepthi Kolady:
LaTeX: Language Pattern-aware Triggering Event Detection for Adverse Experience during Pandemics. CoRR abs/2310.03941 (2023) - [i7]Shengkun Wang, Yangxiao Bai, Kaiqun Fu, Linhan Wang, Chang-Tien Lu, Taoran Ji:
ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction. CoRR abs/2310.18706 (2023) - [i6]Shengkun Wang, Yangxiao Bai, Taoran Ji, Kaiqun Fu, Linhan Wang, Chang-Tien Lu:
Stock Movement and Volatility Prediction from Tweets, Macroeconomic Factors and Historical Prices. CoRR abs/2312.03758 (2023) - 2022
- [j2]Yanshen Sun, Yen-Cheng Lu, Kaiqun Fu, Fanglan Chen, Chang-Tien Lu:
Detecting anomalous traffic behaviors with seasonal deep Kalman filter graph convolutional neural networks. J. King Saud Univ. Comput. Inf. Sci. 34(8 Part A): 4729-4742 (2022) - [c19]Guangyu Meng, Qisheng Jiang, Kaiqun Fu, Beiyu Lin, Chang-Tien Lu, Zhiqian Chen:
Early Forecast of Traffic Accident Impact Based on a Single-Snapshot Observation (Student Abstract). AAAI 2022: 13015-13016 - [c18]Jason Wang, Kaiqun Fu, Zhiqian Chen, Chang-Tien Lu:
Augmentation of Chinese Character Representations with Compositional Graph Learning (Student Abstract). AAAI 2022: 13075-13076 - [c17]Zonghan Zhang, Subhodip Biswas, Fanglan Chen, Kaiqun Fu, Taoran Ji, Chang-Tien Lu, Naren Ramakrishnan, Zhiqian Chen:
Blocking Influence at Collective Level with Hard Constraints (Student Abstract). AAAI 2022: 13115-13116 - [c16]Zibo Liu, Kaiqun Fu, Xiaotong Liu:
Multi-view Cascading Spatial-Temporal Graph Neural Network for Traffic Flow Forecasting. ICANN (2) 2022: 605-616 - [c15]Lei Zhang, Kaiqun Fu, Taoran Ji, Chang-Tien Lu:
Granger Causal Inference for Interpretable Traffic Prediction. ITSC 2022: 1645-1651 - [c14]Guangyu Meng, Qisheng Jiang, Kaiqun Fu, Beiyu Lin, Chang-Tien Lu, Zhqian Chen:
Early Forecasting of the Impact of Traffic Accidents Using a Single Shot Observation. SDM 2022: 100-108 - 2021
- [c13]Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications. AAAI 2021: 7953-7960 - [c12]Kaiqun Fu, Taoran Ji, Nathan Self, Zhiqian Chen, Chang-Tien Lu:
A Hierarchical Attention Graph Convolutional Network for Traffic Incident Impact Forecasting. IEEE BigData 2021: 1619-1624 - [d1]Jason Wang, Kaiqun Fu, Chang-Tien Lu:
Fine-Grained Balanced Cyberbullying Dataset. IEEE DataPort, 2021
- [i5]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu C. Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks. CoRR abs/2107.10234 (2021) - 2020
- [c11]Omer Zulfiqar, Yi-Chun Chang, Po-Han Chen, Kaiqun Fu, Chang-Tien Lu, David Solnick, Yanlin Li:
RISECURE: Metro Incidents And Threat Detection Using Social Media. ASONAM 2020: 531-535 - [c10]Jason Wang, Kaiqun Fu, Chang-Tien Lu:
SOSNet: A Graph Convolutional Network Approach to Fine-Grained Cyberbullying Detection. IEEE BigData 2020: 1699-1708 - [i4]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks. CoRR abs/2002.11867 (2020)
2010 – 2019
- 2019
- [j1]Kaiqun Fu, Abdulaziz Alhamadani, Taoran Ji, Chang-Tien Lu:
Batman or the joker?: the powerful urban computing and its ethics issues. ACM SIGSPATIAL Special 11(2): 16-25 (2019) - [c9]Taoran Ji, Xuchao Zhang, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Feature driven learning framework for cybersecurity event detection. ASONAM 2019: 196-203 - [c8]Kaiqun Fu, Taoran Ji, Liang Zhao, Chang-Tien Lu:
TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction. SIGSPATIAL/GIS 2019: 329-338 - [c7]Taoran Ji, Zhiqian Chen, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks. IJCAI 2019: 2621-2627 - [i3]Taoran Ji, Zhiqian Chen, Nathan Self, Kaiqun Fu, Chang-Tien Lu, Naren Ramakrishnan:
Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks. CoRR abs/1905.10022 (2019) - [i2]Kaiqun Fu, Taoran Ji, Liang Zhao, Chang-Tien Lu:
TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction. CoRR abs/1911.08684 (2019) - 2018
- [c6]Taoran Ji, Kaiqun Fu, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan:
Multi-Task Learning for Transit Service Disruption Detection. ASONAM 2018: 634-641 - [c5]Kaiqun Fu, Zhiqian Chen, Chang-Tien Lu:
StreetNet: preference learning with convolutional neural network on urban crime perception. SIGSPATIAL/GIS 2018: 269-278 - 2017
- [i1]Weisheng Zhong, Fanglan Chen, Kaiqun Fu, Chang-Tien Lu:
SAFEBIKE: A Bike-sharing Route Recommender with Availability Prediction and Safe Routing. CoRR abs/1712.01469 (2017) - 2015
- [c4]Kaiqun Fu, Weisheng Zhong, Chang-Tien Lu, Arnold P. Boedihardjo:
Find the butterfly: a social media based arterial incidents detection and causality analysis system. SIGSPATIAL/GIS 2015: 99:1-99:4 - [c3]Kaiqun Fu, Chang-Tien Lu, Rakesh Nune, Jason Xianding Tao:
Steds: Social Media Based Transportation Event Detection with Text Summarization. ITSC 2015: 1952-1957 - 2014
- [c2]Meiling Liu, Kaiqun Fu, Chang-Tien Lu, Guangsheng Chen, Huiqiang Wang:
A search and summary application for traffic events detection based on Twitter data. SIGSPATIAL/GIS 2014: 549-552 - [c1]Kaiqun Fu, Yen-Cheng Lu, Chang-Tien Lu:
TREADS: a safe route recommender using social media mining and text summarization. SIGSPATIAL/GIS 2014: 557-560
Coauthor Index
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last updated on 2025-01-20 22:59 CET by the dblp team
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