1 code implementation • 29 Apr 2024 • Yiyuan Yang, Ming Jin, Haomin Wen, Chaoli Zhang, Yuxuan Liang, Lintao Ma, Yi Wang, Chenghao Liu, Bin Yang, Zenglin Xu, Jiang Bian, Shirui Pan, Qingsong Wen
Conditioned models, on the other hand, utilize extra information to enhance performance and are similarly divided for both predictive and generative tasks.
no code implementations • 26 Mar 2024 • Hang Li, Tianlong Xu, Jiliang Tang, Qingsong Wen
Knowledge concept tagging for questions plays a crucial role in contemporary intelligent educational applications, including learning progress diagnosis, practice question recommendations, and course content organization.
no code implementations • 26 Mar 2024 • Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen
The advent of Large Language Models (LLMs) has brought in a new era of possibilities in the realm of education.
1 code implementation • 25 Mar 2024 • Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, Yuxuan Liang
Urban indicator prediction aims to infer socio-economic metrics in diverse urban landscapes using data-driven methods.
1 code implementation • 22 Mar 2024 • Yifan Zhang, Weiqi Chen, Zhaoyang Zhu, Dalin Qin, Liang Sun, Xue Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin
For the state-of-the-art (SOTA) model, the MSE is reduced by $33. 3\%$.
no code implementations • 21 Mar 2024 • Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen
Time series analysis stands as a focal point within the data mining community, serving as a cornerstone for extracting valuable insights crucial to a myriad of real-world applications.
1 code implementation • 21 Mar 2024 • Wei Chen, Yuxuan Liang, Yuanshao Zhu, Yanchuan Chang, Kang Luo, Haomin Wen, Lei LI, Yanwei Yu, Qingsong Wen, Chao Chen, Kai Zheng, Yunjun Gao, Xiaofang Zhou, Yu Zheng
In this paper, we present a comprehensive review of the development and recent advances in deep learning for trajectory computing (DL4Traj).
1 code implementation • 15 Mar 2024 • Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan
This enables the effective evaluation of the well-trained GNNs' ability to capture test node semantics and structural representations, making it an expressive metric for estimating the generalization error in online GNN evaluation.
no code implementations • 13 Mar 2024 • Richard Tong, Haoyang Li, Joleen Liang, Qingsong Wen
Finally, we outline a strategic roadmap for stakeholders to implement these standards, fostering a cohesive and ethical AIED ecosystem.
1 code implementation • 8 Mar 2024 • Yi-Fan Zhang, Weichen Yu, Qingsong Wen, Xue Wang, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
In the realms of computer vision and natural language processing, Large Vision-Language Models (LVLMs) have become indispensable tools, proficient in generating textual descriptions based on visual inputs.
no code implementations • 25 Feb 2024 • shiyi qi, Zenglin Xu, Yiduo Li, Liangjian Wen, Qingsong Wen, Qifan Wang, Yuan Qi
Recent advancements in deep learning have led to the development of various models for long-term multivariate time-series forecasting (LMTF), many of which have shown promising results.
1 code implementation • 19 Feb 2024 • Hezhe Qiao, Qingsong Wen, XiaoLi Li, Ee-Peng Lim, Guansong Pang
This work considers a practical semi-supervised graph anomaly detection (GAD) scenario, where part of the nodes in a graph are known to be normal, contrasting to the unsupervised setting in most GAD studies with a fully unlabeled graph.
no code implementations • 18 Feb 2024 • Jiaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang
In long-term time series forecasting (LTSF) tasks, existing deep learning models overlook the crucial characteristic that discrete time series originate from underlying continuous dynamic systems, resulting in a lack of extrapolation and evolution capabilities.
3 code implementations • 6 Feb 2024 • Jun Wang, Wenjie Du, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, Qingsong Wen
In this paper, we conduct a comprehensive survey on the recently proposed deep learning imputation methods.
3 code implementations • 5 Feb 2024 • Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, Qingsong Wen
Time series analysis is essential for comprehending the complexities inherent in various real-world systems and applications.
1 code implementation • 4 Feb 2024 • Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo
Multi-scale division divides the time series into different temporal resolutions using patches of various sizes.
1 code implementation • 3 Feb 2024 • Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun
Time series forecasting is an important and forefront task in many real-world applications.
no code implementations • 2 Feb 2024 • Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen, Jing Liang, Xing Fan, Haoyang Li, Jiliang Tang, Qingsong Wen
The recent surge in generative AI technologies, such as large language models and diffusion models, have boosted the development of AI applications in various domains, including science, finance, and education.
1 code implementation • 16 Jan 2024 • Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen
Explaining multivariate time series is a compound challenge, as it requires identifying important locations in the time series and matching complex temporal patterns.
no code implementations • 10 Jan 2024 • Shubao Zhao, Ming Jin, Zhaoxiang Hou, Chengyi Yang, Zengxiang Li, Qingsong Wen, Yi Wang
Time series forecasting is crucial and challenging in the real world.
no code implementations • 26 Nov 2023 • Feiyi Chen, Yingying Zhang, Zhen Qin, Lunting Fan, Renhe Jiang, Yuxuan Liang, Qingsong Wen, Shuiguang Deng
Anomaly detection significantly enhances the robustness of cloud systems.
no code implementations • 16 Nov 2023 • Yangze Zhou, Qingsong Wen, Jie Song, Xueyuan Cui, Yi Wang
Accurate load forecasting serves as the foundation for the flexible operation of multi-energy systems (MES).
no code implementations • 25 Oct 2023 • Zefan Wang, Zichuan Liu, Yingying Zhang, Aoxiao Zhong, Lunting Fan, Lingfei Wu, Qingsong Wen
Large language model (LLM) applications in cloud root cause analysis (RCA) have been actively explored recently.
1 code implementation • 22 Oct 2023 • Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, Yuxuan Liang
To answer the questions, we leverage the power of Large Language Models (LLMs) and introduce the first-ever LLM-enhanced framework that integrates the knowledge of textual modality into urban imagery profiling, named LLM-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining (UrbanCLIP).
5 code implementations • 16 Oct 2023 • Ming Jin, Qingsong Wen, Yuxuan Liang, Chaoli Zhang, Siqiao Xue, Xue Wang, James Zhang, Yi Wang, Haifeng Chen, XiaoLi Li, Shirui Pan, Vincent S. Tseng, Yu Zheng, Lei Chen, Hui Xiong
In this survey, we offer a comprehensive and up-to-date review of large models tailored (or adapted) for time series and spatio-temporal data, spanning four key facets: data types, model categories, model scopes, and application areas/tasks.
no code implementations • 9 Oct 2023 • Feiyi Chen, Zhen Qin, Yingying Zhang, Shuiguang Deng, Yi Xiao, Guansong Pang, Qingsong Wen
Retraining a large neural network model with limited data is vulnerable to overfitting.
1 code implementation • 3 Oct 2023 • 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
We begin by reprogramming the input time series with text prototypes before feeding it into the frozen LLM to align the two modalities.
1 code implementation • NeurIPS 2023 • Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao
Deep learning (DL) techniques have recently found success in anomaly detection (AD) across various fields such as finance, medical services, and cloud computing.
1 code implementation • NeurIPS 2023 • Yi-Fan Zhang, Qingsong Wen, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
Online updating of time series forecasting models aims to address the concept drifting problem by efficiently updating forecasting models based on streaming data.
no code implementations • 28 Aug 2023 • Shikai Fang, Qingsong Wen, Yingtao Luo, Shandian Zhe, Liang Sun
More importantly, almost all methods assume the observations are sampled at regular time stamps, and fail to handle complex irregular sampled time series arising from different applications.
1 code implementation • 10 Aug 2023 • Siqiao Xue, Fan Zhou, Yi Xu, Ming Jin, Qingsong Wen, Hongyan Hao, Qingyang Dai, Caigao Jiang, Hongyu Zhao, Shuo Xie, Jianshan He, James Zhang, Hongyuan Mei
We present WeaverBird, an intelligent dialogue system designed specifically for the finance domain.
1 code implementation • 16 Jul 2023 • Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, Caigao Jiang, Chen Pan, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei
In this paper, we present EasyTPP, the first central repository of research assets (e. g., data, models, evaluation programs, documentations) in the area of event sequence modeling.
1 code implementation • 14 Jul 2023 • Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Leandro Von Krannichfeldt, Yi Wang
Based on this, we conducted extensive experiments on load data at different levels, providing a reference for researchers to compare different load forecasting models.
1 code implementation • 7 Jul 2023 • Ming Jin, Huan Yee Koh, Qingsong Wen, Daniele Zambon, Cesare Alippi, Geoffrey I. Webb, Irwin King, Shirui Pan
In this survey, we provide a comprehensive review of graph neural networks for time series analysis (GNN4TS), encompassing four fundamental dimensions: forecasting, classification, anomaly detection, and imputation.
2 code implementations • 17 Jun 2023 • Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
On the other hand, contrastive learning aims to find a representation that can clearly distinguish any instance from the others, which can bring a more natural and promising representation for time series anomaly detection.
1 code implementation • 16 Jun 2023 • Kexin Zhang, Qingsong Wen, Chaoli Zhang, Rongyao Cai, Ming Jin, Yong liu, James Zhang, Yuxuan Liang, Guansong Pang, Dongjin Song, Shirui Pan
To fill this gap, we review current state-of-the-art SSL methods for time series data in this article.
no code implementations • 14 Jun 2023 • Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun
In this paper, we propose a novel forecasting framework, named Self-adaptive Decomposed Interpretable framework~(SaDI), which ensembles long-term trend, short-term trend, and period modelings to capture temporal characteristics in different components.
no code implementations • 31 May 2023 • Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Yi Wang
The uncertainties in load forecasting can be divided into two types: epistemic uncertainty and aleatoric uncertainty.
1 code implementation • 20 May 2023 • Wang Xue, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin
In this work, we design a special Transformer, i. e., Channel Aligned Robust Blend Transformer (CARD for short), that addresses key shortcomings of CI type Transformer in time series forecasting.
no code implementations • 11 May 2023 • Ming Jin, Guangsi Shi, Yuan-Fang Li, Qingsong Wen, Bo Xiong, Tian Zhou, Shirui Pan
In this paper, we establish a theoretical framework that unravels the expressive power of spectral-temporal GNNs.
no code implementations • 7 Mar 2023 • Zhiqiang Zhou, Chaoli Zhang, Lingna Ma, Jing Gu, Huajie Qian, Qingsong Wen, Liang Sun, Peng Li, Zhimin Tang
This paper discusses horizontal POD resources management in Alibaba Cloud Container Services with a newly deployed AI algorithm framework named AHPA -- the adaptive horizontal pod auto-scaling system.
no code implementations • 6 Mar 2023 • Qingsong Wen, Linxiao Yang, Liang Sun
In this paper, we propose a robust and effective periodicity detection algorithm for time series with block missing data.
1 code implementation • 31 Jan 2023 • Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, Yuxuan Liang
Spatio-temporal graph neural networks (STGNN) have emerged as the dominant model for spatio-temporal graph (STG) forecasting.
1 code implementation • 29 Nov 2022 • Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, Roger Zimmermann
Air pollution is a crucial issue affecting human health and livelihoods, as well as one of the barriers to economic and social growth.
1 code implementation • 24 Oct 2022 • Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
The goal of sequential event prediction is to estimate the next event based on a sequence of historical events, with applications to sequential recommendation, user behavior analysis and clinical treatment.
1 code implementation • 18 Oct 2022 • Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
Time series anomaly detection is a challenging problem due to the complex temporal dependencies and the limited label data.
no code implementations • 24 Jun 2022 • Tian Zhou, Jianqing Zhu, Xue Wang, Ziqing Ma, Qingsong Wen, Liang Sun, Rong Jin
Various deep learning models, especially some latest Transformer-based approaches, have greatly improved the state-of-art performance for long-term time series forecasting. However, those transformer-based models suffer a severe deterioration performance with prolonged input length, which prohibits them from using extended historical info. Moreover, these methods tend to handle complex examples in long-term forecasting with increased model complexity, which often leads to a significant increase in computation and less robustness in performance(e. g., overfitting).
no code implementations • 7 Jun 2022 • Xiaomin Song, Qingsong Wen, Yan Li, Liang Sun
Dynamic time warping (DTW) is an effective dissimilarity measure in many time series applications.
3 code implementations • 18 May 2022 • Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
Recent studies have shown that deep learning models such as RNNs and Transformers have brought significant performance gains for long-term forecasting of time series because they effectively utilize historical information.
Ranked #3 on Time Series Forecasting on ETTh2 (96) Univariate
no code implementations • 1 Apr 2022 • Miha Grabner, Yi Wang, Qingsong Wen, Boštjan Blažič, Vitomir Štruc
Efficient load forecasting is needed to ensure better observability in the distribution networks, whereas such forecasting is made possible by an increasing number of smart meter installations.
no code implementations • 23 Feb 2022 • Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun
Localizing the root cause of network faults is crucial to network operation and maintenance.
10 code implementations • 15 Feb 2022 • Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun
From the perspective of network structure, we summarize the adaptations and modifications that have been made to Transformers in order to accommodate the challenges in time series analysis.
3 code implementations • 30 Jan 2022 • Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin
Although Transformer-based methods have significantly improved state-of-the-art results for long-term series forecasting, they are not only computationally expensive but more importantly, are unable to capture the global view of time series (e. g. overall trend).
no code implementations • 5 Nov 2021 • Yingying Zhang, Zhengxiong Guan, Huajie Qian, Leili Xu, Hengbo Liu, Qingsong Wen, Liang Sun, Junwei Jiang, Lunting Fan, Min Ke
As business of Alibaba expands across the world among various industries, higher standards are imposed on the service quality and reliability of big data cloud computing platforms which constitute the infrastructure of Alibaba Cloud.
no code implementations • 18 Sep 2021 • Linxiao Yang, Qingsong Wen, Bo Yang, Liang Sun
Many real-world time series exhibit multiple seasonality with different lengths.
no code implementations • 3 Mar 2021 • Qingyang Xu, Qingsong Wen, Liang Sun
By incorporating the learned long-range structure, the second stage can enhance the prediction accuracy in the forecast horizon.
no code implementations • 27 Feb 2020 • Qingsong Wen, Liang Sun, Fan Yang, Xiaomin Song, Jingkun Gao, Xue Wang, Huan Xu
In this paper, we systematically review different data augmentation methods for time series.
no code implementations • 21 Feb 2020 • Jingkun Gao, Xiaomin Song, Qingsong Wen, Pichao Wang, Liang Sun, Huan Xu
It is deployed as a public online service and widely adopted in different business scenarios at Alibaba Group.
1 code implementation • 21 Feb 2020 • Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu
Periodicity detection is a crucial step in time series tasks, including monitoring and forecasting of metrics in many areas, such as IoT applications and self-driving database management system.
1 code implementation • 10 Jun 2019 • Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Jian Tan
Extracting the underlying trend signal is a crucial step to facilitate time series analysis like forecasting and anomaly detection.
1 code implementation • 5 Dec 2018 • Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu
Based on the extracted trend, we apply the the non-local seasonal filtering to extract the seasonality component.