Listed by categories in reversed chronological order, where + indicates equal contribution and * denotes the corresponding author.
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, Yuxuan Liang*
A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects
Haomin Wen, Youfang Lin, Lixia Wu, Xiaowei Mao, Tianyue Cai, Yunfeng Hou, Shengnan Guo, Yuxuan Liang, Guangyin Jin, Yiji Zhao, Roger Zimmermann, Jieping Ye, Huaiyu Wan
Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts
Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang*, Yuankai Wu, Roger Zimmermann, Yang Wang*
Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan
Semantic-fused multi-granularity cross-city traffic prediction
Kehua Chen, Yuxuan Liang, Jindong Han, Siyuan Feng, Meixin Zhu, Hai Yang
On regularization for explaining graph neural networks: An information theory perspective
Junfeng Fan, Guibin Zhang, Kun Wang, Wenjie Du, Yifan Duan, Yuankai Wu, Roger Zimmermann, Xiaowen Chu, Yuxuan Liang*
Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth
Wei Chen, Xixuan Hao, Yuankai Wu, Yuxuan Liang*
NeurIPS 2024 (Datasets and Benchmarks Track)
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forcasting
Qiangxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang*
Attractor memory for long-term time series forecasting: A chaos perspective
Jaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang*
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
Guibin Zhang, Haonan Dong, Yuchen Zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang
NeurIPS 2024
Improving Generalization of Dynamic Graph Learning via Environment Prompt
Kuo Yang, Zhengyang Zhou, Qihe Huang, Limin Li, Yuxuan Liang, Yang Wang
NeurIPS 2024
Towards unifying diffusion models for probabilistic spatio-temporal graph learningJunfeng Hu, Xu Liu, Zhencheng Fan, Yuxuan Liang*, Roger Zimmermann
SIGSPATIAL 2024
UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation
Siru Zhong, Yuxuan Liang, Yibo Yan, Ying Zhang, Yangqiu Song, Yuxuan Liang*
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*
Reinventing Node-Centric Traffic Forecasting for Improved Accuracy and Efficiency
Xu Liu, Yuxuan Liang*, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann
ECML-PKDD 2024
The Heterophily Snowflake Hypothesis: Training and Empowering GNN for Heterophilic Graphs
Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang*, Yang Wang*
Controltraj: Controllable trajectory generation with topology-constrained diffusion model
Yuanshao Zhu, James Jianqiao Yu*, Xiangyu Zhao*, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, Yuxuan Liang*
Cluster-Wide Task Slowdown Detection in Cloud System
Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng
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, Xiaojiang Peng, Yuxuan Liang*, Yang Wang*
Position Paper: 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*
LaDe: The first comprehensive last-mile delivery dataset from industry
Lixia Wu, Haomin Wen, Haoyuan Hu, Xiaowei Mao, Yutong Xia, Ergang Shan, Jianbin Zhen, Junhong Lou, Yuxuan Liang*, Liuqing Yang, others
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
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
Predicting Parking 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*
Spatio-Temporal Field Neural Networks for Air Quality Inference
Yutong Feng, Qiongyan Wang, Yutong Xia, Junlin Huang, Siru Zhong, Yuxuan Liang*
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
Kang Luo, Yuanshao Zhu, Wei Chen, Kun Wang, Zhengyang Zhou, Sijie Ruan, Yuxuan Liang*
Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Anomaly Detection
Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng
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*
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
COLA: Cross-city Mobility Transformer for Human Trajectory Simulation
Yu Wang, Tongya Zheng, Yuxuan Liang, Shunyu Liu, Mingli Song
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*
Graph Lottery Ticket Automated
Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng*, Yuxuan Liang*
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
Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
Hao Wu, Shilong Wang, Yuxuan Liang, Zhengyang Zhou, Wei Huang, Wei Xiong, Kun Wang
MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting
Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu*
SENCR: A Span Enhanced Two-stage Network with Counterfactual Rethinking for Chinese NER
Hang Zheng, Qingsong Li, Shen Chen, Yuxuan Liang, Li Liu*
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
CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting
Chengxin Wang, Yuxuan Liang, Gary Tan
WSDM 2024 PDF
Fall Prediction by a Spatio-Temporal Multi-Channel Causal Model from Wearable Sensors Data
Guorui Liao, Jiawei Liu, Yuxuan Liang, Shu Wang, Li Liu*
Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets
Kun Wang, Yuxuan Liang*, Xinglin Li, Guohao Li, Bernard Ghanem, Roger Zimmermann, Zhengyang Zhou, huahui Yi, Yudong Zhang, Yang Wang*
Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey
Guangyin Jin, Yuxuan Liang*, Yuchen Fang, Jincai Huang, Junbo Zhang, Yu Zheng
Predicting collective human mobility via countering spatiotemporal heterogeneity
Zhengyang Zhou, Kuo Yang, Yuxuan Liang, Binwu Wang, Hongyang Chen, Yang Wang
Decoupling Long-and Short-Term Patterns in Spatiotemporal Inference
Junfeng Hu, Yuxuan Liang*, Zhencheng Fan, Li Liu, Yifang Yin, Roger Zimmermann
AutoSTG+: An Automatic Framework to Discover The Optimal Network for Spatio-temporal Graph Prediction
Songyu Ke, Zheyi Pan, Tianfu He, Yuxuan Liang, Junbo Zhang, Yu Zheng
End-to-end Delay Modeling via Leveraging Competitive Interaction among Network Flows
Weiping Zheng, Minli Hong, Ruihao Ye, Xiaomao Fan, Yuxuan Liang, Gansen Zhao, Roger Zimmermann
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
Yutong Xia, Yuxuan Liang*, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting (DB Track)
Xu Liu, Yutong Xia, Yuxuan Liang*, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenquang Liu, Brvan Hooi, Roger Zimmermann
Graph Neural Processes for Spatio-Temporal Extrapolation
Junfeng Hu, Yuxuan Liang*, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann
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
Contrastive Trajectory Similarity Learning with Dual-Feature Attention
Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, Egemen Tanin
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
Kun Wang, Yuxuan Liang*, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang*
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
PetalView: Fine-grained Location and Orientation Extraction of Street-view Images via Cross-view Local Search
Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Yifang Yin, Xianjing Han, Hannes Kruppa, See-Kiong Ng, Roger Zimmermann
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, Yuxuan Liang*
Primacy Effect of ChatGPT
Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi
Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Zheyi Pan, Yifang Yin, Hongyang Chen, Junbo Zhang, Yu Zheng, David S Rosenblum, Roger Zimmermann
Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery
Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Yifang Yin, Andrei Georgescu, An Tran, Hannes Kruppa, See-Kiong Ng, Roger Zimmermann
When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?
Xu Liu+, Yuxuan Liang+, Chao Huang, Yu Zheng, Bryan Hooi, and Roger Zimmermann
Dualformer: Local-global stratified transformer for efficient video recognition
Yuxuan Liang, Pan Zhou, Roger Zimmermann, Shuicheng Yan
TrajFormer: Efficient Trajectory Classification with Transformers
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Xu Liu, Hongyang Chen, Junbo Zhang, Yu Zheng, Roger Zimmermann
Periodic Residual Learning for Crowd Flow Forecasting
Chengxin Wang, Yuxuan Liang, Gary Tan
Time-Aware Neighbor Sampling on Temporal Graphs
Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi
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
Visual Cascade Analytics of Large-Scale Spatiotemporal Data
Zikun Deng, Di Weng, Yuxuan Liang, Jie Bao, Yu Zheng, Tobias Schreck, Mingliang Xu, Yingcai Wu
Modeling Trajectories with Neural Ordinary Differential Equations
Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann
Fine-grained Urban Flow Prediction
Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, Roger Zimmermann
AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph
Zheyi Pan, Songyu Ke, Xiaodu Yang, Yuxuan Liang, Yong Yu, Junbo Zhang, Yu Zheng
Mixup for Node and Graph Classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi
Curgraph: Curriculum learning for graph classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi
Directed Graph Contrastive Learning
Zekun Tong, Yuxuan Liang, Henghui Ding, Yongxing Dai, Xinke Li, Changhu Wang
Adaptive Data Augmentation on Temporal Graphs
Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi
Learning Multi-context Aware Location Representations from Large-scale Geotagged Images
Yifang Yin, Ying Zhang, Zhenguang Liu, Yuxuan Liang, Sheng Wang, Rajiv Ratn Shah, Roger Zimmermann
Fine-grained Urban Flow Inference
Kun Ouyang, Yuxuan Liang, Ye Liu, Zekun Tong, Sijie Ruan, David Rosenblum, Yu Zheng
Predicting Citywide Crowd Flows in Irregular Regions using Multi-View Graph Convolutional Networks
Junkai Sun, Junbo Zhang, Qiaofei Li, Xiuwen Yi, Yuxuan Liang, Yu Zheng
Spatio-Temporal Meta Learning for Urban Traffic Prediction
Zheyi Pan, Wentao Zhang, Yuxuan Liang, Weinan Zhang, Yong Yu, Junbo Zhang, Yu Zheng
Predicting Urban Water Quality with Ubiquitous Data – a Data-Driven Approach
Ye Liu, Yuxuan Liang, Kun Ouyang, Shuming Liu, David Rosenblum, Yu Zheng
Nodeaug: Semi-Supervised Node Classification with Data Augmentation
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi
Digraph Inception Convolutional Networks
Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, Andrew Lim
Revisiting convolutional neural networks for citywide crowd flow analytics
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S Rosenblum
Autost: Efficient Neural Architecture Search for Spatio-Temporal Prediction
Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, Yu Zheng
Dynamic Public Resource Allocation based on Human Mobility Prediction
Sijie Ruan, Jie Bao, Yuxuan Liang, Ruiyuan Li, Tianfu He, Chuishi Meng, Yanhua Li, Yingcai Wu, Yu Zheng
Learning to Generate Maps from Trajectories
Sijie Ruan, Cheng Long, Jie Bao, Chunyang Li, Zisheng Yu, Ruiyuan Li, Yuxuan Liang, Tianfu He, Yu Zheng
Progressive Supervision for Node Classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi
Unsupervised Learning of Disentangled Location Embeddings
Kun Ouyang, Yuxuan Liang, Ye Liu, David S Rosenblum, Wenzhuo Yang
Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang
Urbanfm: Inferring Fine-Grained Urban Flows
Yuxuan Liang+, Kun Ouyang+, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S Rosenblum, Yu Zheng
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
GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction.
Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, Yu Zheng
Inferring Traffic Cascading Patterns
Yuxuan Liang, Zhongyuan Jiang, Yu Zheng
Urban Water Quality Prediction based on Multi-Task Multi-View Learning
Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, David S Rosenblum
Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts
Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang*, Yuankai Wu, Roger Zimmermann, Yang Wang*
Semantic-fused multi-granularity cross-city traffic prediction
Kehua Chen, Yuxuan Liang, Jindong Han, Siyuan Feng, Meixin Zhu, Hai Yang
Towards unifying diffusion models for probabilistic spatio-temporal graph learningJunfeng Hu, Xu Liu, Zhencheng Fan, Yuxuan Liang*, Roger Zimmermann
SIGSPATIAL 2024
Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth
Wei Chen, Xixuan Hao, Yuankai Wu, Yuxuan Liang*
NeurIPS 2024 (Datasets and Benchmarks Track)
Reinventing Node-Centric Traffic Forecasting for Improved Accuracy and Efficiency
Xu Liu, Yuxuan Liang*, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann
ECML-PKDD 2024
Controltraj: Controllable trajectory generation with topology-constrained diffusion model
Yuanshao Zhu, James Jianqiao Yu*, Xiangyu Zhao*, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, Yuxuan Liang*
Cluster-Wide Task Slowdown Detection in Cloud System
Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng
Position Paper: 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*
LaDe: The first comprehensive last-mile delivery dataset from industry
Lixia Wu, Haomin Wen, Haoyuan Hu, Xiaowei Mao, Yutong Xia, Ergang Shan, Jianbin Zhen, Junhong Lou, Yuxuan Liang*, Liuqing Yang, others
Predicting Parking 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*
Spatio-Temporal Field Neural Networks for Air Quality Inference
Yutong Feng, Qiongyan Wang, Yutong Xia, Junlin Huang, Siru Zhong, Yuxuan Liang*
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
Kang Luo, Yuanshao Zhu, Wei Chen, Kun Wang, Zhengyang Zhou, Sijie Ruan, Yuxuan Liang*
Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Anomaly Detection
Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng
COLA: Cross-city Mobility Transformer for Human Trajectory Simulation
Yu Wang, Tongya Zheng, Yuxuan Liang, Shunyu Liu, Mingli Song
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*
Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
Hao Wu, Shilong Wang, Yuxuan Liang, Zhengyang Zhou, Wei Huang, Wei Xiong, Kun Wang
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
CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting
Chengxin Wang, Yuxuan Liang, Gary Tan
WSDM 2024 PDF
Fall Prediction by a Spatio-Temporal Multi-Channel Causal Model from Wearable Sensors Data
Guorui Liao, Jiawei Liu, Yuxuan Liang, Shu Wang, Li Liu*
Predicting collective human mobility via countering spatiotemporal heterogeneity
Zhengyang Zhou, Kuo Yang, Yuxuan Liang, Binwu Wang, Hongyang Chen, Yang Wang
Decoupling Long-and Short-Term Patterns in Spatiotemporal Inference
Junfeng Hu, Yuxuan Liang*, Zhencheng Fan, Li Liu, Yifang Yin, Roger Zimmermann
AutoSTG+: An Automatic Framework to Discover The Optimal Network for Spatio-temporal Graph Prediction
Songyu Ke, Zheyi Pan, Tianfu He, Yuxuan Liang, Junbo Zhang, Yu Zheng
End-to-end Delay Modeling via Leveraging Competitive Interaction among Network Flows
Weiping Zheng, Minli Hong, Ruihao Ye, Xiaomao Fan, Yuxuan Liang, Gansen Zhao, Roger Zimmermann
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
Yutong Xia, Yuxuan Liang*, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting (DB Track)
Xu Liu, Yutong Xia, Yuxuan Liang*, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenquang Liu, Brvan Hooi, Roger Zimmermann
Graph Neural Processes for Spatio-Temporal Extrapolation
Junfeng Hu, Yuxuan Liang*, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann
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
Contrastive Trajectory Similarity Learning with Dual-Feature Attention
Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, Egemen Tanin
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
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, Yuxuan Liang*
Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Zheyi Pan, Yifang Yin, Hongyang Chen, Junbo Zhang, Yu Zheng, David S Rosenblum, Roger Zimmermann
When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?
Xu Liu+, Yuxuan Liang+, Chao Huang, Yu Zheng, Bryan Hooi, and Roger Zimmermann
TrajFormer: Efficient Trajectory Classification with Transformers
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Xu Liu, Hongyang Chen, Junbo Zhang, Yu Zheng, Roger Zimmermann
Periodic Residual Learning for Crowd Flow Forecasting
Chengxin Wang, Yuxuan Liang, Gary Tan
Time-Aware Neighbor Sampling on Temporal Graphs
Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi
Visual Cascade Analytics of Large-Scale Spatiotemporal Data
Zikun Deng, Di Weng, Yuxuan Liang, Jie Bao, Yu Zheng, Tobias Schreck, Mingliang Xu, Yingcai Wu
Modeling Trajectories with Neural Ordinary Differential Equations
Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann
Fine-grained Urban Flow Prediction
Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, Roger Zimmermann
AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph
Zheyi Pan, Songyu Ke, Xiaodu Yang, Yuxuan Liang, Yong Yu, Junbo Zhang, Yu Zheng
Fine-grained Urban Flow Inference
Kun Ouyang, Yuxuan Liang, Ye Liu, Zekun Tong, Sijie Ruan, David Rosenblum, Yu Zheng
Spatio-Temporal Meta Learning for Urban Traffic Prediction
Zheyi Pan, Wentao Zhang, Yuxuan Liang, Weinan Zhang, Yong Yu, Junbo Zhang, Yu Zheng
Predicting Citywide Crowd Flows in Irregular Regions using Multi-View Graph Convolutional Networks
Junkai Sun, Junbo Zhang, Qiaofei Li, Xiuwen Yi, Yuxuan Liang, Yu Zheng
Yang Liu, Yingting Liu, Zhijie Liu, Yuxuan Liang, Chuishi Meng, Junbo Zhang, Yu Zheng
Predicting Urban Water Quality with Ubiquitous Data – a Data-Driven Approach
Ye Liu, Yuxuan Liang, Kun Ouyang, Shuming Liu, David Rosenblum, Yu Zheng
Revisiting convolutional neural networks for citywide crowd flow analytics
Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S Rosenblum
Autost: Efficient Neural Architecture Search for Spatio-Temporal Prediction
Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, Yu Zheng
Dynamic Public Resource Allocation based on Human Mobility Prediction
Sijie Ruan, Jie Bao, Yuxuan Liang, Ruiyuan Li, Tianfu He, Chuishi Meng, Yanhua Li, Yingcai Wu, Yu Zheng
Learning to Generate Maps from Trajectories
Sijie Ruan, Cheng Long, Jie Bao, Chunyang Li, Zisheng Yu, Ruiyuan Li, Yuxuan Liang, Tianfu He, Yu Zheng
Unsupervised Learning of Disentangled Location Embeddings
Kun Ouyang, Yuxuan Liang, Ye Liu, David S Rosenblum, Wenzhuo Yang
Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning
Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang
Urbanfm: Inferring Fine-Grained Urban Flows
Yuxuan Liang+, Kun Ouyang+, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S Rosenblum, Yu Zheng
GeoMAN: Multi-Level Attention Networks for Geo-sensory Time Series Prediction.
Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, Yu Zheng
Inferring Traffic Cascading Patterns
Yuxuan Liang, Zhongyuan Jiang, Yu Zheng
Urban Water Quality Prediction based on Multi-Task Multi-View Learning
Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, David S Rosenblum
Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan
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
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forcasting
Qiangxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang*
Attractor memory for long-term time series forecasting: A chaos perspective
Jaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang*
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
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*
Position Paper: 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*
MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting
Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu*
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, Yuxuan Liang*
UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation
Siru Zhong, Yuxuan Liang, Yibo Yan, Ying Zhang, Yangqiu Song, Yuxuan Liang
MM 2024 PDF CODE 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*
PetalView: Fine-grained Location and Orientation Extraction of Street-view Images via Cross-view Local Search
Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Yifang Yin, Xianjing Han, Hannes Kruppa, See-Kiong Ng, Roger Zimmermann
Dualformer: Local-global stratified transformer for efficient video recognition
Yuxuan Liang, Pan Zhou, Roger Zimmermann, Shuicheng Yan
Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery
Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Yifang Yin, Andrei Georgescu, An Tran, Hannes Kruppa, See-Kiong Ng, Roger Zimmermann
Learning Multi-context Aware Location Representations from Large-scale Geotagged Images
Yifang Yin, Ying Zhang, Zhenguang Liu, Yuxuan Liang, Sheng Wang, Rajiv Ratn Shah, Roger Zimmermann
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
On regularization for explaining graph neural networks: An information theory perspective
Junfeng Fan, Guibin Zhang, Kun Wang, Wenjie Du, Yifan Duan, Yuankai Wu, Roger Zimmermann, Xiaowen Chu, Yuxuan Liang*
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
GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
Guibin Zhang, Haonan Dong, Yuchen Zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang
NeurIPS 2024
Improving Generalization of Dynamic Graph Learning via Environment Prompt
Kuo Yang, Zhengyang Zhou, Qihe Huang, Limin Li, Yuxuan Liang, Yang Wang
NeurIPS 2024
The Heterophily Snowflake Hypothesis: Training and Empowering GNN for Heterophilic Graphs
Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang*, Yang Wang*
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
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, Xiaojiang Peng, Yuxuan Liang*, Yang Wang*
Graph Lottery Ticket Automated
Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng*, Yuxuan Liang*
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
Kun Wang, Yuxuan Liang*, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang*
Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets
Kun Wang, Yuxuan Liang*, Xinglin Li, Guohao Li, Bernard Ghanem, Roger Zimmermann, Zhengyang Zhou, huahui Yi, Yudong Zhang, Yang Wang*
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li
Curgraph: Curriculum learning for graph classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi
Directed Graph Contrastive Learning
Zekun Tong, Yuxuan Liang, Henghui Ding, Yongxing Dai, Xinke Li, Changhu Wang
Mixup for Node and Graph Classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi
Adaptive Data Augmentation on Temporal Graphs
Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi
Nodeaug: Semi-Supervised Node Classification with Data Augmentation
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi
Digraph Inception Convolutional Networks
Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, Andrew Lim
Progressive Supervision for Node Classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, Yuxuan Liang*
A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects
Haomin Wen, Youfang Lin, Lixia Wu, Xiaowei Mao, Tianyue Cai, Yunfeng Hou, Shengnan Guo, Yuxuan Liang, Guangyin Jin, Yiji Zhao, Roger Zimmermann, Jieping Ye, Huaiyu Wan
Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong Liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan
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*
Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey
Guangyin Jin, Yuxuan Liang*, Yuchen Fang, Jincai Huang, Junbo Zhang, Yu Zheng
SENCR: A Span Enhanced Two-stage Network with Counterfactual Rethinking for Chinese NER
Hang Zheng, Qingsong Li, Shen Chen, Yuxuan Liang, Li Liu*
Primacy Effect of ChatGPT
Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi
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
Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation
Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li
Yang Liu, Yingting Liu, Zhijie Liu, Yuxuan Liang, Chuishi Meng, Junbo Zhang, Yu Zheng
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