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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)- 2023
- [j3]Dongjie Wang, Yanjie Fu, Kunpeng Liu, Fanglan Chen, Pengyang Wang, Chang-Tien Lu:
Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluation. ACM Trans. Spatial Algorithms Syst. 9(1): 2:1-2:24 (2023) - [j2]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Memetic Algorithms for Spatial Partitioning Problems. ACM Trans. Spatial Algorithms Syst. 9(1): 5:1-5:31 (2023) - [c15]Fanglan Chen, Subhodip Biswas, Zhiqian Chen, Shuo Lei, Naren Ramakrishnan, Chang-Tien Lu:
Exploring Tradeoffs in Automated School Redistricting: Computational and Ethical Perspectives. AAAI 2023: 15912-15920 - [c14]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation. ACL (1) 2023: 11014-11026 - [c13]Jianfeng He, Xuchao Zhang, Shuo Lei, Abdulaziz Alhamadani, Fanglan Chen, Bei Xiao, Chang-Tien Lu:
CLUR: Uncertainty Estimation for Few-Shot Text Classification with Contrastive Learning. KDD 2023: 698-710 - [i10]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
TART: Improved Few-shot Text Classification Using Task-Adaptive Reference Transformation. CoRR abs/2306.02175 (2023) - 2022
- [j1]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) - [c12]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 - [c11]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Bowen Du, Chang-Tien Lu:
Cross-Domain Few-Shot Semantic Segmentation. ECCV (30) 2022: 73-90 - [c10]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels. NAACL-HLT (Findings) 2022: 1987-1997 - [i9]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Sampling-based techniques for designing school boundaries. CoRR abs/2206.03703 (2022) - [i8]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Memetic algorithms for Spatial Partitioning problems. CoRR abs/2208.02867 (2022) - 2021
- [c9]Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information. ASONAM 2021: 168-175 - [c8]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
Few-Shot Semantic Segmentation via Prototype Augmentation with Image-Level Annotations. ICME 2021: 1-6 - [i7]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) - [i6]Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu:
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information. CoRR abs/2111.05199 (2021) - [i5]Dongjie Wang, Yanjie Fu, Kunpeng Liu, Fanglan Chen, Pengyang Wang, Chang-Tien Lu:
Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluation. CoRR abs/2112.14699 (2021) - 2020
- [c7]Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu:
Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. AAAI 2020: 6853-6860 - [c6]Subhodip Biswas, Fanglan Chen, Andreea Sistrunk, Sathappan Muthiah, Zhiqian Chen, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan:
Geospatial Clustering for Balanced and Proximal Schools. AAAI 2020: 13358-13365 - [c5]Jianfeng He, Xuchao Zhang, Shuo Lei, Zhiqian Chen, Fanglan Chen, Abdulaziz Alhamadani, Bei Xiao, Chang-Tien Lu:
Towards More Accurate Uncertainty Estimation In Text Classification. EMNLP (1) 2020: 8362-8372 - [c4]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Chang-Tien Lu, Naren Ramakrishnan:
Incorporating domain knowledge into Memetic Algorithms for solving Spatial Optimization problems. SIGSPATIAL/GIS 2020: 25-35 - [c3]Fanglan Chen, Zhiqian Chen, Subhodip Biswas, Shuo Lei, Naren Ramakrishnan, Chang-Tien Lu:
Graph Convolutional Networks with Kalman Filtering for Traffic Prediction. SIGSPATIAL/GIS 2020: 135-138 - [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) - [i3]Shuo Lei, Xuchao Zhang, Jianfeng He, Fanglan Chen, Chang-Tien Lu:
Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations. CoRR abs/2007.01496 (2020)
2010 – 2019
- 2019
- [c2]Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Andreea Sistrunk, Nathan Self, Chang-Tien Lu, Naren Ramakrishnan:
REGAL: A Regionalization framework for school boundaries. SIGSPATIAL/GIS 2019: 544-547 - [c1]Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan:
Mitigating Uncertainty in Document Classification. NAACL-HLT (1) 2019: 3126-3136 - [i2]Xuchao Zhang, Fanglan Chen, Chang-Tien Lu, Naren Ramakrishnan:
Mitigating Uncertainty in Document Classification. CoRR abs/1907.07590 (2019) - 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)
Coauthor Index
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