Liang, Yuxuan

58 publications

NeurIPS 2025 Aeolus: A Multi-Structural Flight Delay Dataset Lin Xu, Xinyun Yuan, Yuxuan Liang, Suwan Yin, Yuankai Wu

ICLR 2025 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

AAAI 2025 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

IJCAI 2025 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

ICLR 2025 Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting Wei Chen, Yuxuan Liang

NeurIPS 2025 FlowNet: Modeling Dynamic Spatio-Temporal Systems via Flow Propagation Yutong Feng, Xu Liu, Yutong Xia, Yuxuan Liang

NeurIPS 2025 Improving Bilinear RNN with Closed-Loop Control Jiaxi Hu, Yongqi Pan, Jusen Du, Disen Lan, Xiaqiang Tang, Qingsong Wen, Yuxuan Liang, Weigao Sun

NeurIPS 2025 Learning to Factorize Spatio-Temporal Foundation Models Siru Zhong, Junjie Qiu, Yangyu Wu, Xingchen Zou, Zhongwen Rao, Bin Yang, Chenjuan Guo, Hao Xu, Yuxuan Liang

NeurIPS 2025 Learning with Calibration: Exploring Test-Time Computing of Spatio-Temporal Forecasting Wei Chen, Yuxuan Liang

ICML 2025 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

NeurIPS 2025 Not All Data Are Good Labels: On the Self-Supervised Labeling for Time Series Forecasting Yuxuan Yang, Dalin Zhang, Yuxuan Liang, Hua Lu, Gang Chen, Huan Li

ICLR 2025 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

AAAI 2025 Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach Qingxiang Liu, Sheng Sun, Yuxuan Liang, Min Liu, Jingjing Xue

NeurIPS 2025 Recognition Through Reasoning: Reinforcing Image Geo-Localization with Large Vision-Language Models Ling Li, Yao Zhou, Yuxuan Liang, Fugee Tsung, Jiaheng Wei

IJCAI 2025 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

ECML-PKDD 2025 ST-LoRA: Low-Rank Adaptation for Spatio-Temporal Forecasting Weilin Ruan, Wei Chen, Xilin Dang, Jianxiang Zhou, Weichuang Li, Xu Liu, Yuxuan Liang

NeurIPS 2025 ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models Bosong Huang, Ming Jin, Yuxuan Liang, Johan Barthelemy, Debo Cheng, Qingsong Wen, Chenghao Liu, Shirui Pan

AAAI 2025 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

ICML 2025 Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Siru Zhong, Weilin Ruan, Ming Jin, Huan Li, Qingsong Wen, Yuxuan Liang

ICLR 2025 Towards Neural Scaling Laws for Time Series Foundation Models Qingren Yao, Chao-Han Huck Yang, Renhe Jiang, Yuxuan Liang, Ming Jin, Shirui Pan

AAAI 2025 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

AAAI 2025 UniTR: A Unified Framework for Joint Representation Learning of Trajectories and Road Networks Jie Zhao, Chao Chen, Yuanshao Zhu, Mingyu Deng, Yuxuan Liang

NeurIPS 2025 UniTraj: Learning a Universal Trajectory Foundation Model from Billion-Scale Worldwide Traces Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao, Xun Zhou, Liang Han, Xuetao Wei, Yuxuan Liang

AAAI 2025 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

AAAI 2025 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

NeurIPS 2024 Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective Jiaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang

AAAI 2024 Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model Hao Wu, Yuxuan Liang, Wei Xiong, Zhengyang Zhou, Wei Huang, Shilong Wang, Kun Wang

NeurIPS 2024 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

ICLR 2024 Graph Lottery Ticket Automated Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang

NeurIPS 2024 Improving Generalization of Dynamic Graph Learning via Environment Prompt Kuo Yang, Zhengyang Zhou, Qihe Huang, Limin Li, Yuxuan Liang, Yang Wang

AAAI 2024 MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu

ICML 2024 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

ICLR 2024 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

ICML 2024 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

IJCAI 2024 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

ECML-PKDD 2024 Reinventing Node-Centric Traffic Forecasting for Improved Accuracy and Efficiency Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann

AAAI 2024 SENCR: A Span Enhanced Two-Stage Network with Counterfactual Rethinking for Chinese NER Hang Zheng, Qingsong Li, Shen Chen, Yuxuan Liang, Li Liu

IJCAI 2024 Spatio-Temporal Field Neural Networks for Air Quality Inference Yutong Feng, Qiongyan Wang, Yutong Xia, Junlin Huang, Siru Zhong, Yuxuan Liang

NeurIPS 2024 Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth Wei Chen, Xixuan Hao, Yuankai Wu, Yuxuan Liang

NeurIPS 2024 Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang

ICLR 2024 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

IJCAI 2024 Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning Kang Luo, Yuanshao Zhu, Wei Chen, Kun Wang, Zhengyang Zhou, Sijie Ruan, Yuxuan Liang

ICML 2024 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

AAAI 2023 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

NeurIPS 2023 Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, Roger Zimmermann

NeurIPS 2023 LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann

ICLR 2023 Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang

ECCV 2022 DualFormer: Local-Global Stratified Transformer for Efficient Video Recognition Yuxuan Liang, Pan Zhou, Roger Zimmermann, Shuicheng Yan

NeurIPS 2021 Adaptive Data Augmentation on Temporal Graphs Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi

NeurIPS 2021 Directed Graph Contrastive Learning Zekun Tong, Yuxuan Liang, Henghui Ding, Yongxing Dai, Xinke Li, Changhu Wang

IJCAI 2021 Modeling Trajectories with Neural Ordinary Differential Equations Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann

NeurIPS 2020 Digraph Inception Convolutional Networks Zekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David Rosenblum, Andrew Lim

AAAI 2020 Learning to Generate Maps from Trajectories Sijie Ruan, Cheng Long, Jie Bao, Chunyang Li, Zisheng Yu, Ruiyuan Li, Yuxuan Liang, Tianfu He, Yu Zheng

ECML-PKDD 2020 Progressive Supervision for Node Classification Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi

ECML-PKDD 2020 Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S. Rosenblum

IJCAI 2019 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

IJCAI 2018 GeoMAN: Multi-Level Attention Networks for Geo-Sensory Time Series Prediction Yuxuan Liang, Songyu Ke, Junbo Zhang, Xiuwen Yi, Yu Zheng

IJCAI 2016 Urban Water Quality Prediction Based on Multi-Task Multi-View Learning Ye Liu, Yu Zheng, Yuxuan Liang, Shuming Liu, David S. Rosenblum