Yuxuan Liang
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
101
Venues
17
Active years
2016–2026
Best venue rank
A*
Where they publish
Papers
101 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting. | Sisuo Lyu, Siru Zhong, Weilin Ruan, Qingxiang Liu, Qingsong Wen, Hui Xiong, Yuxuan Liang |
| 2026 | AAAI | A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction. | Weilin Ruan, Xilin Dang, Ziyu Zhou, Sisuo Lyu, Yuxuan Liang |
| 2026 | AAAI | Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting. | Ziyu Zhou, Yiming Huang, Yanyun Wang, Yuankai Wu, James Kwok, Yuxuan Liang |
| 2026 | ACL | Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models. | Zhiqing Cui, Binwu Wang, Qingxiang Liu, Yeqiang Wang, Zhengyang Zhou, Yuxuan Liang, Yang Wang |
| 2026 | ACL | Traffic-R1: Reinforced LLMs Bring Human-Like Reasoning to Traffic Signal Control Systems. | Xingchen Zou, Yuhao Yang, Zheng Chen, Xixuan Hao, Yiqi Chen, Chao Huang, Yuxuan Liang |
| 2026 | ICDE | Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction. | Rui An, Yifeng Zhang, Ziran Liang, Wenqi Fan, Yuxuan Liang, Xuequn Shang, Qing Li |
| 2026 | KDD | How to Train Your Mamba for Time Series Forecasting. | Jiaxi Hu, Disen Lan, Ziyu Zhou, Gefeng Luo, Qingsong Wen, Yuxuan Liang |
| 2026 | KDD | FaST: Efficient and Effective Long-Horizon Forecasting for Large-Scale Spatial-Temporal Graphs via Mixture-of-Experts. | Yiji Zhao, Zihao Zhong, Ao Wang, Haomin Wen, Ming Jin, Yuxuan Liang, Huaiyu Wan, Hao Wu |
| 2026 | WWW | Efficient High-Dimensional Time Series Forecasting with Transformers: A Channel Reordering Perspective. | Yuchen Fang, Shiyu Wang, Yuxuan Liang, Zhou Ye, Yang Xiang, Yan Zhao, Kai Zheng |
| 2026 | WWW | AgentSense: LLMs Empower Generalizable and Explainable Web-Based Participatory Urban Sensing. | Xusen Guo, Mingxing Peng, Xixuan Hao, Xingchen Zou, Qiongyan Wang, Sijie Ruan, Yuxuan Liang |
| 2026 | WWW | Enhancing Ride-Hailing Forecasting at DiDi with Multi-View Geospatial Representation Learning from the Web. | Xixuan Hao, Guicheng Li, Daiqiang Wu, Xusen Guo, Yumeng Zhu, Zhichao Zou, Peng Zhen, Yao Yao, Yuxuan Liang |
| 2026 | WWW | Eclipse Attacks on Ethereum's Peer-to-Peer Network. | Ruisheng Shi, Yuxuan Liang, Zijun Guo, Qin Wang, Lina Lan, Chenfeng Wang, Zhuoyi Zheng |
| 2026 | WWW | LLM-Enhanced Web-Centric Spatio-Temporal Intelligence: Methods, Applications, and Frontier Research. | Zijian Zhang, Hao Miao, Yuxuan Liang, Yan Zhao, Irwin King |
| 2025 | AAAI | UniTR: A Unified Framework for Joint Representation Learning of Trajectories and Road Networks. | Jie Zhao, Chao Chen, Yuanshao Zhu, Mingyu Deng, Yuxuan Liang |
| 2025 | AAAI | UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction. | Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, Yuxuan Liang |
| 2025 | AAAI | Unlocking the Power of LSTM for Long Term Time Series Forecasting. | Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen |
| 2025 | AAAI | Towards Scalable and Deep Graph Neural Networks via Noise Masking. | Yuxuan Liang, Wentao Zhang, Zeang Sheng, Ling Yang, Quanqing Xu, Jiawei Jiang, Yunhai Tong, Bin Cui |
| 2025 | AAAI | Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach. | Qingxiang Liu, Sheng Sun, Yuxuan Liang, Min Liu, Jingjing Xue |
| 2025 | AAAI | AirRadar: Inferring Nationwide Air Quality in China with Deep Neural Networks. | Qiongyan Wang, Yutong Xia, Siru Zhong, Weichuang Li, Yuankai Wu, Shifen Cheng, Junbo Zhang, Yu Zheng, Yuxuan Liang |
| 2025 | AAAI | Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classifications. | Yutong Xia, Runpeng Yu, Yuxuan Liang, Xavier Bresson, Xinchao Wang, Roger Zimmermann |
| 2025 | CIKM | The International Workshop on Spatio-Temporal Data Intelligence and Foundation Models. | Hao Miao, Yan Zhao, Yuxuan Liang, Bin Yang, Kai Zheng, Christian S. Jensen |
| 2025 | EMNLP | GraphAgent: Agentic Graph Language Assistant. | Yuhao Yang, Jiabin Tang, Lianghao Xia, Xingchen Zou, Yuxuan Liang, Chao Huang |
| 2025 | ICDE | AdaMove: Efficient Test-Time Adaptation for Human Mobility Prediction. | Huaxu Han, Shuliang Wang, Sijie Ruan, Qianyu Yang, Yuxuan Liang, Ziqiang Yuan, Cheng Long, Hanning Yuan, Yu Zheng |
| 2025 | ICDE | Training-Free Heterogeneous Graph Condensation via Data Selection. | Yuxuan Liang, Wentao Zhang, Xinyi Gao, Ling Yang, Chong Chen, Hongzhi Yin, Yunhai Tong, Bin Cui |
| 2025 | ICDE | Data Driven Decision Making with Time Series and Spatio-Temporal Data. | Bin Yang, Yuxuan Liang, Chenjuan Guo, Christian S. Jensen |
| 2025 | ICDM | Test-Time Graph Rebirth for GNN Generalization Under Distribution Shifts. | Xin Zheng, Bo Li, Yu Zheng, Qin Zhang, Haishuai Wang, Yuxuan Liang, Alan Wee-Chung Liew, Shirui Pan |
| 2025 | ICLR | Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting. | Wei Chen, Yuxuan Liang |
| 2025 | ICLR | Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics. | Zaige Fei, Fan Xu, Junyuan Mao, Yuxuan Liang, Qingsong Wen, Kun Wang, Hao Wu, Yang Wang |
| 2025 | ICLR | Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems. | Jindong Tian, Yuxuan Liang, Ronghui Xu, Peng Chen, Chenjuan Guo, Aoying Zhou, Lujia Pan, Zhongwen Rao, Bin Yang |
| 2025 | ICLR | Towards Neural Scaling Laws for Time Series Foundation Models. | Qingren Yao, Chao-Han Huck Yang, Renhe Jiang, Yuxuan Liang, Ming Jin, Shirui Pan |
| 2025 | ICML | Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts. | Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Junnan Li, Silvio Savarese, Caiming Xiong, Doyen Sahoo |
| 2025 | ICML | Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting. | Siru Zhong, Weilin Ruan, Ming Jin, Huan Li, Qingsong Wen, Yuxuan Liang |
| 2025 | IJCAI | Deep Learning for Multivariate Time Series Imputation: A Survey. | Jun Wang, Wenjie Du, Yiyuan Yang, Linglong Qian, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, Qingsong Wen |
| 2025 | IJCAI | Reinforcement Learning for Hybrid Charging Stations Planning and Operation Considering Fixed and Mobile Chargers. | Yanchen Zhu, Honghui Zou, Chufan Liu, Yuyu Luo, Yuankai Wu, Yuxuan Liang |
| 2025 | KDD | Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective. | Yuchen Fang, Yuxuan Liang, Bo Hui, Zezhi Shao, Liwei Deng, Xu Liu, Xinke Jiang, Kai Zheng |
| 2025 | KDD | The 14th International Workshop on Urban Computing. | Yuxuan Liang, Yu Zheng, Chuishi Meng, Yanhua Li, Jieping Ye, Philip S. Yu, Ouri Wolfson |
| 2025 | KDD | Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey. | Yuxuan Liang, Haomin Wen, Yutong Xia, Ming Jin, Bin Yang, Flora Salim, Qingsong Wen, Shirui Pan, Gao Cong |
| 2025 | KDD | The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Yuxuan Liang, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2025 | KDD | DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting. | Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Yuxuan Liang, Yu Zheng, Qingsong Wen, Kun Wang |
| 2025 | KDD | Learning Generalized and Flexible Trajectory Models from Omni-Semantic Supervision. | Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao, Xiao Han, Qidong Liu, Xuetao Wei, Yuxuan Liang |
| 2025 | KDD | Fine-grained Urban Heat Island Effect Forecasting: A Context-aware Thermodynamic Modeling Framework. | Xingchen Zou, Weilin Ruan, Siru Zhong, Yuehong Hu, Yuxuan Liang |
| 2025 | WWW | Time Series Analysis in the Web: Recent Advances and Future Trends. | Ming Jin, Wei Jin, Hao Xue, Flora Salim, Yuxuan Liang |
| 2025 | WWW | The Workshop of Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications. | Ming Jin, Mahsa Salehi, Yuxuan Liang, Dongjin Song, Flora Salim, Min Wu, Shirui Pan, Qingsong Wen |
| 2025 | WWW | Nature Makes No Leaps: Building Continuous Location Embeddings with Satellite Imagery from the Web. | Xixuan Hao, Wei Chen, Xingchen Zou, Yuxuan Liang |
| 2025 | WWW | The International Workshop on Spatio-Temporal Data Mining from the Web. | Yuxuan Liang, Hao Xue, Ming Jin, Flora Salim, Qingsong Wen, Yong Li, Roger Zimmermann, Yu Zheng |
| 2025 | WWW | Web-Centric Human Mobility Analytics: Methods, Applications, and Future Directions in the LLM Era. | Zijian Zhang, Hao Miao, Yuxuan Liang, Yan Zhao, Xiao Han, Pengyue Jia, Bin Yang, Christian S. Jensen |
| 2024 | AAAI | MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting. | Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu |
| 2024 | AAAI | Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model. | Hao Wu, Yuxuan Liang, Wei Xiong, Zhengyang Zhou, Wei Huang, Shilong Wang, Kun Wang |
| 2024 | AAAI | SENCR: A Span Enhanced Two-Stage Network with Counterfactual Rethinking for Chinese NER. | Hang Zheng, Qingsong Li, Shen Chen, Yuxuan Liang, Li Liu |
| 2024 | ICASSP | Fall Prediction by a Spatio-Temporal Multi-Channel Causal Model from Wearable Sensors Data. | Guorui Liao, Jiawei Liu, Yuxuan Liang, Shu Wang, Li Liu |
| 2024 | ICDE | Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection. | Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng |
| 2024 | ICDE | HGAMLP: Heterogeneous Graph Attention MLP with De-Redundancy Mechanism. | Yuxuan Liang, Wentao Zhang, Zeang Sheng, Ling Yang, Jiawei Jiang, Yunhai Tong, Bin Cui |
| 2024 | ICDE | Urban Sensing for Multi-Destination Workers via Deep Reinforcement Learning. | Shuliang Wang, Song Tang, Sijie Ruan, Cheng Long, Yuxuan Liang, Qi Li, Ziqiang Yuan, Jie Bao, Yu Zheng |
| 2024 | ICLR | Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. | Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen |
| 2024 | ICLR | NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling. | Kun Wang, Hao Wu, Yifan Duan, Guibin Zhang, Kai Wang, Xiaojiang Peng, Yu Zheng, Yuxuan Liang, Yang Wang |
| 2024 | ICLR | Graph Lottery Ticket Automated. | Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang |
| 2024 | ICML | Position: What Can Large Language Models Tell Us about Time Series Analysis. | Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen |
| 2024 | ICML | Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness. | Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen |
| 2024 | ICML | Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching. | Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, Yang You |
| 2024 | IJCAI | Spatio-Temporal Field Neural Networks for Air Quality Inference. | Yutong Feng, Qiongyan Wang, Yutong Xia, Junlin Huang, Siru Zhong, Yuxuan Liang |
| 2024 | IJCAI | Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning. | Kang Luo, Yuanshao Zhu, Wei Chen, Kun Wang, Zhengyang Zhou, Sijie Ruan, Yuxuan Liang |
| 2024 | IJCAI | Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach. | Huaiwu Zhang, Yutong Xia, Siru Zhong, Kun Wang, Zekun Tong, Qingsong Wen, Roger Zimmermann, Yuxuan Liang |
| 2024 | IJCNN | GSDI: Spatio-Temporal Contrastive Learning for Geo-Sensory Data Inference. | Songyu Ke, Yuxuan Liang, Xiuwen Yi, Junbo Zhang, Yu Zheng |
| 2024 | KDD | Cluster-Wide Task Slowdown Detection in Cloud System. | Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng |
| 2024 | KDD | The 13th International Workshop on Urban Computing. | Yuxuan Liang, Chuishi Meng, Yanhua Li, Yu Zheng, Jieping Ye, Qiang Yang, Philip S. Yu, Ouri Wolfson |
| 2024 | KDD | Foundation Models for Time Series Analysis: A Tutorial and Survey. | Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen |
| 2024 | KDD | The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field. | Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Junfeng Fang, Xiaojiang Peng, Yuxuan Liang, Yang Wang |
| 2024 | KDD | The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs. | Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang |
| 2024 | KDD | LaDe: The First Comprehensive Last-mile Express Dataset from Industry. | Lixia Wu, Haomin Wen, Haoyuan Hu, Xiaowei Mao, Yutong Xia, Ergang Shan, Jianbin Zheng, Junhong Lou, Yuxuan Liang, Liuqing Yang, Roger Zimmermann, Youfang Lin, Huaiyu Wan |
| 2024 | KDD | ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model. | Yuanshao Zhu, James Jian Qiao Yu, Xiangyu Zhao, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, Yuxuan Liang |
| 2024 | WWW | UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting. | Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann |
| 2024 | WWW | COLA: Cross-city Mobility Transformer for Human Trajectory Simulation. | Yu Wang, Tongya Zheng, Yuxuan Liang, Shunyu Liu, Mingli Song |
| 2024 | WWW | UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web. | Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, Yuxuan Liang |
| 2024 | WSDM | CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting. | Chengxin Wang, Yuxuan Liang, Gary Tan |
| 2023 | AAAI | AirFormer: Predicting Nationwide Air Quality in China with Transformers. | Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, Roger Zimmermann |
| 2023 | CoNLL | How Fragile is Relation Extraction under Entity Replacements? | Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen |
| 2023 | EMNLP | Primacy Effect of ChatGPT. | Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi |
| 2023 | ICDE | Contrastive Trajectory Similarity Learning with Dual-Feature Attention. | Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, Egemen Tanin |
| 2023 | ICLR | Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective. | Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang |
| 2023 | KDD | Graph Neural Processes for Spatio-Temporal Extrapolation. | Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann |
| 2023 | KDD | Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning. | Zhengyang Zhou, Qihe Huang, Kuo Yang, Kun Wang, Xu Wang, Yudong Zhang, Yuxuan Liang, Yang Wang |
| 2022 | CIKM | TrajFormer: Efficient Trajectory Classification with Transformers. | Yuxuan Liang, Kun Ouyang, Yiwei Wang, Xu Liu, Hongyang Chen, Junbo Zhang, Yu Zheng, Roger Zimmermann |
| 2022 | ECCV | DualFormer: Local-Global Stratified Transformer for Efficient Video Recognition. | Yuxuan Liang, Pan Zhou, Roger Zimmermann, Shuicheng Yan |
| 2022 | IJCNN | Time-Aware Neighbor Sampling on Temporal Graphs. | Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi |
| 2022 | KDD | Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation. | Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li |
| 2022 | NAACL | GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction. | Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Bryan Hooi |
| 2022 | NAACL | Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis. | Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, Bryan Hooi |
| 2021 | IJCAI | Modeling Trajectories with Neural Ordinary Differential Equations. | Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann |
| 2021 | WWW | Fine-Grained Urban Flow Prediction. | Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David S. Rosenblum, Roger Zimmermann |
| 2021 | WWW | AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph✱. | Zheyi Pan, Songyu Ke, Xiaodu Yang, Yuxuan Liang, Yong Yu, Junbo Zhang, Yu Zheng |
| 2021 | WWW | CurGraph: Curriculum Learning for Graph Classification. | Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi |
| 2021 | WWW | Mixup for Node and Graph Classification. | Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi |
| 2020 | AAAI | Learning to Generate Maps from Trajectories. | Sijie Ruan, Cheng Long, Jie Bao, Chunyang Li, Zisheng Yu, Ruiyuan Li, Yuxuan Liang, Tianfu He, Yu Zheng |
| 2020 | IJCNN | Unsupervised Learning of Disentangled Location Embeddings. | Kun Ouyang, Yuxuan Liang, Ye Liu, David S. Rosenblum, Wenzhuo Yang |
| 2020 | KDD | AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction. | Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, Yu Zheng |
| 2020 | KDD | NodeAug: Semi-Supervised Node Classification with Data Augmentation. | Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi |
| 2019 | IJCAI | Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking. | Nirandika Wanigasekara, Yuxuan Liang, Siong Thye Goh, Ye Liu, Joseph Jay Williams, David S. Rosenblum |
| 2019 | KDD | UrbanFM: Inferring Fine-Grained Urban Flows. | Yuxuan Liang, Kun Ouyang, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S. Rosenblum, Yu Zheng |
| 2019 | KDD | Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning. | Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang |
| 2018 | IJCAI | GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction. | Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, Yu Zheng |
| 2016 | IJCAI | Urban Water Quality Prediction Based on Multi-Task Multi-View Learning. | Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, David S. Rosenblum |