Chang Xu - RankMe

43 papers A* 14A 3Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgentGC: Evolutionary Learning-based Lossless Compression for Genomics Data with LLM-driven Multiple Agent. CoRR Sun Hui, Yanfeng Ding, Huidong Ma, Chang Xu, Keyan Jin, Lizheng Zu, Cheng Zhong, Xiaoguang Liu, Gang Wang, Wentong Cai
2026	A*	`conf`	Controllable Financial Market Generation with Diffusion Guided Meta Agent. AAAI Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
2026	J	`jnl`	Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition. CoRR Dongyuan Li, Shun Zheng, Chang Xu, Jiang Bian, Renhe Jiang
2025	A*	`conf`	BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling. ICML Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian
2025	J	`jnl`	BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modelling. CoRR Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian
2025	J	`jnl`	Causal Time Series Generation via Diffusion Models. CoRR Yutong Xia, Chang Xu, Yuxuan Liang, Qingsong Wen, Roger Zimmermann, Jiang Bian
2025	A*	`conf`	Does Acceleration Cause Hidden Instability in Vision Language Models? Uncovering Instance-Level Divergence Through a Large-Scale Empirical Study. EMNLP Yizheng Sun, Hao Li, Chang Xu, Hongpeng Zhou, Chenghua Lin, Riza Batista-Navarro, Jingyuan Sun
2025	—	`conf`	InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models. KDD (1) Min Hou, Yueying Wu, Chang Xu, Yu-Hao Huang, Chenxi Bai, Le Wu, Jiang Bian
2025	J	`jnl`	MIRA: Medical Time Series Foundation Model for Real-World Health Data. CoRR Hao Li, Bowen Deng, Chang Xu, Zhiyuan Feng, Viktor Schlegel, Yu-Hao Huang, Yizheng Sun, Jingyuan Sun, Kailai Yang, Yiyao Yu, Jiang Bian
2025	A*	`conf`	MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model. ICLR Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
2025	J	`jnl`	Silent Hazards of Token Reduction in Vision-Language Models: The Hidden Impact on Consistency. CoRR Yizheng Sun, Hao Li, Chang Xu, Chenghua Lin, Riza Batista-Navarro, Jingyuan Sun
2025	—	`conf`	TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation. KDD (2) Bowen Deng, Chang Xu, Hao Li, Yu-Hao Huang, Min Hou, Jiang Bian
2025	J	`jnl`	TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation. CoRR Bowen Deng, Chang Xu, Hao Li, Yuhao Huang, Min Hou, Jiang Bian
2025	A*	`conf`	TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts. AAAI Yu-Hao Huang, Chang Xu, Yueying Wu, Wu-Jun Li, Jiang Bian
2025	J	`jnl`	TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts. CoRR Yu-Hao Huang, Chang Xu, Yueying Wu, Wu-Jun Li, Jiang Bian
2025	J	`jnl`	TimeRAF: Retrieval-Augmented Foundation Model for Zero-Shot Time Series Forecasting. IEEE Trans. Knowl. Data Eng. Huanyu Zhang, Chang Xu, Yifan Zhang, Zhang Zhang, Liang Wang, Jiang Bian
2024	J	`jnl`	A multimodal stepwise-coordinating framework for pedestrian trajectory prediction. Knowl. Based Syst. Yijun Wang, Zekun Guo, Chang Xu, Jianxin Lin
2024	J	`jnl`	Controllable Financial Market Generation with Diffusion Guided Meta Agent. CoRR Yu-Hao Huang, Chang Xu, Yang Liu, Weiqing Liu, Wu-Jun Li, Jiang Bian
2024	J	`jnl`	Digger-Guider: High-Frequency Factor Extraction for Stock Trend Prediction. IEEE Trans. Knowl. Data Eng. Yang Liu, Chang Xu, Min Hou, Weiqing Liu, Jiang Bian, Qi Liu, Tie-Yan Liu
2024	J	`jnl`	InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models. CoRR Min Hou, Yueying Wu, Chang Xu, Yu-Hao Huang, Chenxi Bai, Le Wu, Jiang Bian
2024	A*	`conf`	MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process. ICLR Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
2024	J	`jnl`	MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process. CoRR Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
2024	J	`jnl`	MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model. CoRR Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian
2024	J	`jnl`	TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting. CoRR Huanyu Zhang, Chang Xu, Yifan Zhang, Zhang Zhang, Liang Wang, Jiang Bian, Tieniu Tan
2023	J	`jnl`	Efficient Behavior-consistent Calibration for Multi-agent Market Simulation. CoRR Tianlang He, Keyan Lu, Chang Xu, Yang Liu, Weiqing Liu, S.-H. Gary Chan, Jiang Bian
2023	J	`jnl`	Microstructure-Empowered Stock Factor Extraction and Utilization. CoRR Xianfeng Jiao, Zizhong Li, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian
2022	A*	`conf`	Learning Differential Operators for Interpretable Time Series Modeling. KDD Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
2022	J	`jnl`	Learning Differential Operators for Interpretable Time Series Modeling. CoRR Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
2022	A*	`conf`	Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction. WWW Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
2021	A*	`conf`	REST: Relational Event-driven Stock Trend Forecasting. WWW Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021	J	`jnl`	REST: Relational Event-driven Stock Trend Forecasting. CoRR Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021	A	`conf`	Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion. CIKM Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, Tie-Yan Liu
2019	A*	`conf`	Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks. AAAI Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu
2019	A*	`conf`	Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models. IJCAI Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu
2018	J	`jnl`	Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks. CoRR Chang Xu, Weiran Huang, Hongwei Wang, Gang Wang, Tie-Yan Liu
2017	A	`conf`	Convolutional neural networks for posed and spontaneous expression recognition. ICME Chang Xu, Tao Qin, Yalong Bai, Gang Wang, Tie-Yan Liu
2017	J	`jnl`	Reinforcement Learning for Learning Rate Control. CoRR Chang Xu, Tao Qin, Gang Wang, Tie-Yan Liu
2016	J	`jnl`	Health Status Assessment and Failure Prediction for Hard Drives with Recurrent Neural Networks. IEEE Trans. Computers Chang Xu, Gang Wang, Xiaoguang Liu, Dongdong Guo, Tie-Yan Liu
2015	A*	`conf`	Automatic Image Dataset Construction from Click-through Logs Using Deep Neural Network. ACM Multimedia Yalong Bai, Kuiyuan Yang, Wei Yu, Chang Xu, Wei-Ying Ma, Tiejun Zhao
2014	A*	`conf`	Bag-of-Words Based Deep Neural Network for Image Retrieval. ACM Multimedia Yalong Bai, Wei Yu, Tianjun Xiao, Chang Xu, Kuiyuan Yang, Wei-Ying Ma, Tiejun Zhao
2014	A	`conf`	RC-NET: A General Framework for Incorporating Knowledge into Word Representations. CIKM Chang Xu, Yalong Bai, Jiang Bian, Bin Gao, Gang Wang, Xiaoguang Liu, Tie-Yan Liu
2014	A*	`conf`	Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. AAAI Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu
2014	J	`jnl`	Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. CoRR Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu