Chang Xu

According to our database, Chang Xu authored at least 33 papers between 2014 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition.

Dongyuan Li, Shun Zheng, Chang Xu, Jiang Bian, Renhe Jiang

CoRR, March, 2026

AgentGC: Evolutionary Learning-based Lossless Compression for Genomics Data with LLM-driven Multiple Agent.

Sun Hui, Yanfeng Ding, Huidong Ma, Chang Xu, Keyan Jin, Lizheng Zu, Cheng Zhong, Xiaoguang Liu, Gang Wang, Wentong Cai

CoRR, January, 2026

Controllable Financial Market Generation with Diffusion Guided Meta Agent.

Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

TimeRAF: Retrieval-Augmented Foundation Model for Zero-Shot Time Series Forecasting.

Huanyu Zhang, Chang Xu, Yifan Zhang, Zhang Zhang, Liang Wang, Jiang Bian

IEEE Trans. Knowl. Data Eng., September, 2025

Causal Time Series Generation via Diffusion Models.

Yutong Xia, Chang Xu, Yuxuan Liang, Qingsong Wen, Roger Zimmermann, Jiang Bian

CoRR, September, 2025

Silent Hazards of Token Reduction in Vision-Language Models: The Hidden Impact on Consistency.

Yizheng Sun, Hao Li, Chang Xu, Chenghua Lin, Riza Batista-Navarro, Jingyuan Sun

CoRR, March, 2025

BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modelling.

Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian

CoRR, March, 2025

MIRA: Medical Time Series Foundation Model for Real-World Health Data.

Hao Li, Bowen Deng, Chang Xu, Zhiyuan Feng, Viktor Schlegel, Yu-Hao Huang, Yizheng Sun, Jingyuan Sun, Kailai Yang, Yiyao Yu, Jiang Bian

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models.

Min Hou, Yueying Wu, Chang Xu, Yu-Hao Huang, Chenxi Bai, Le Wu, Jiang Bian

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation.

Bowen Deng, Chang Xu, Hao Li, Yu-Hao Huang, Min Hou, Jiang Bian

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling.

Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian

Proceedings of the Forty-second International Conference on Machine Learning, 2025

MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model.

Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Does Acceleration Cause Hidden Instability in Vision Language Models? Uncovering Instance-Level Divergence Through a Large-Scale Empirical Study.

Yizheng Sun, Hao Li, Chang Xu, Hongpeng Zhou, Chenghua Lin, Riza Batista-Navarro, Jingyuan Sun

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts.

Yu-Hao Huang, Chang Xu, Yueying Wu, Wu-Jun Li, Jiang Bian

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Digger-Guider: High-Frequency Factor Extraction for Stock Trend Prediction.

Yang Liu, Chang Xu, Min Hou, Weiqing Liu, Jiang Bian, Qi Liu, Tie-Yan Liu

IEEE Trans. Knowl. Data Eng., December, 2024

A multimodal stepwise-coordinating framework for pedestrian trajectory prediction.

Yijun Wang, Zekun Guo, Chang Xu, Jianxin Lin

Knowl. Based Syst., 2024

TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting.

Huanyu Zhang, Chang Xu, Yifan Zhang, Zhang Zhang, Liang Wang, Jiang Bian, Tieniu Tan

CoRR, 2024

MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process.

Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Microstructure-Empowered Stock Factor Extraction and Utilization.

Xianfeng Jiao, Zizhong Li, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian

CoRR, 2023

Efficient Behavior-consistent Calibration for Multi-agent Market Simulation.

Tianlang He, Keyan Lu, Chang Xu, Yang Liu, Weiqing Liu, S.-H. Gary Chan, Jiang Bian

CoRR, 2023

2022

Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction.

Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Learning Differential Operators for Interpretable Time Series Modeling.

Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

REST: Relational Event-driven Stock Trend Forecasting.

Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu

Proceedings of the WWW '21: The Web Conference 2021, 2021

Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion.

Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, Tie-Yan Liu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2019

Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models.

Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks.

Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017

Reinforcement Learning for Learning Rate Control.

Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu

CoRR, 2017

Convolutional neural networks for posed and spontaneous expression recognition.

Chang Xu, Tao Qin, Yalong Bai, Gang Wang, Tie-Yan Liu

Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017

2016

Health Status Assessment and Failure Prediction for Hard Drives with Recurrent Neural Networks.

Chang Xu, Gang Wang, Xiaoguang Liu, Dongdong Guo, Tie-Yan Liu

IEEE Trans. Computers, 2016

2015

Automatic Image Dataset Construction from Click-through Logs Using Deep Neural Network.

Yalong Bai, Kuiyuan Yang, Wei Yu, Chang Xu, Wei-Ying Ma, Tiejun Zhao

Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26, 2015

2014

Bag-of-Words Based Deep Neural Network for Image Retrieval.

Yalong Bai, Wei Yu, Tianjun Xiao, Chang Xu, Kuiyuan Yang, Wei-Ying Ma, Tiejun Zhao

Proceedings of the ACM International Conference on Multimedia, MM '14, Orlando, FL, USA, November 03, 2014

RC-NET: A General Framework for Incorporating Knowledge into Word Representations.

Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, Tie-Yan Liu

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks.

Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014