Fetching the paper…
Reading the bibliography…
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.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901
Earlier work this paper cites.
Attention is all you need. In Advances in Neural Information Processing Systems 30 . 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL-HLT . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Pre-Trained Bidirectional Temporal Representation for Crowd Flows Prediction in Regular Region
Wenying Duan, Liu Jiang, Ning Wang, and Hong Rao. 2019 · 2019
Earlier work this paper cites.
Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting
Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen, Yu-Xiang Wang, and Xifeng Yan. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
A Simple Framework for Contrastive Learning of Visual Representations. In ICML , Vol. 119. 1597–1607
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020 · 2020
Earlier work this paper cites.
Trembr: Exploring Road Networks for Trajectory Representation Learning
Tao-Yang Fu and Wang-Chien Lee. 2020 · 2020
Earlier work this paper cites.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
Earlier work this paper cites.
Adarnn: Adaptive learning and forecasting of time series. In Proceedings of the 30th ACM international conference on information & knowledge management . 402–411
Yuntao Du, Jindong Wang, Wenjie Feng, Sinno Pan, Tao Qin, Renjun Xu, and Chongjun Wang. 2021 · 2021
Earlier work this paper cites.
Recurrent neural networks for time series forecasting: Current status and future directions
Hansika Hewamalage, Christoph Bergmeir, and Kasun Bandara. 2021 · 2021
Earlier work this paper cites.
Reversible instance normalization for accurate time-series forecasting against distribution shift. In International Conference on Learning Representations
Taesung Kim, Jinhee Kim, Yunwon Tae, Cheonbok Park, Jang-Ho Choi, and Jaegul Choo. 2021 · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting. In International Conference on Machine Learning . PMLR, 8857–8868
Kashif Rasul, Calvin Seward, Ingmar Schuster, and Roland Vollgraf. 2021 · 2021
Earlier work this paper cites.
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. In International Conference on Learning Representations
Jiehui Xu, Haixu Wu, Jianmin Wang, and Mingsheng Long. 2021 · 2021
Earlier work this paper cites.
Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, and Yuanqing Xia. 2021 · 2021
Earlier work this paper cites.
Voice2series: Reprogramming acoustic models for time series classification. In International conference on machine learning . PMLR, 11808–11819
Chao-Han Huck Yang, Yun-Yun Tsai, and Pin-Yu Chen. 2021 · 2021
Earlier work this paper cites.
CloudRCA: A root cause analysis framework for cloud computing platforms. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management . 4373–4382
Yingying Zhang, Zhengxiong Guan, Huajie Qian, Leili Xu, Hengbo Liu, Qingsong Wen, Liang Sun, Junwei Jiang, Lunting Fan, and Min Ke. 2021 · 2021
Earlier work this paper cites.
Informer: Beyond efficient transformer for long sequence time-series forecasting. In Proceedings of the AAAI conference on artificial intelligence , Vol. 35. 11106–11115
Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, and Wancai Zhang. 2021 · 2021
Earlier work this paper cites.
Modeling temporal data as continuous functions with process diffusion
Marin Biloš, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, and Stephan Günnemann. 2022 · 2022
Earlier work this paper cites.
Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics
Jiawei Jiang, Dayan Pan, Houxing Ren, Xiaohan Jiang, Chao Li, and Jingyuan Wang. 2022 · 2022
Earlier work this paper cites.
Generative time series forecasting with diffusion, denoise, and disentanglement
Yan Li, Xinjiang Lu, Yaqing Wang, and Dejing Dou. 2022a · 2022
Earlier work this paper cites.
When do contrastive learning signals help spatio-temporal graph forecasting?. In Proceedings of the 30th International Conference on Advances in Geographic Information Systems . 1–12
Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, and Roger Zimmermann. 2022 · 2022
Earlier work this paper cites.
A time series is worth 64 words: Long-term forecasting with transformers
Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam. 2022 · 2022
Earlier work this paper cites.
Contrastive learning for unsupervised domain adaptation of time series
Yilmazcan Ozyurt, Stefan Feuerriegel, and Ce Zhang. 2022 · 2022
Earlier work this paper cites.
Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, et al · 2022
Earlier work this paper cites.
High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
Earlier work this paper cites.
Pre-training enhanced spatial-temporal graph neural network for multivariate time series forecasting. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 1567–1577
Zezhi Shao, Zhao Zhang, Fei Wang, and Yongjun Xu. 2022 · 2022
Earlier work this paper cites.
MTSMAE: Masked Autoencoders for Multivariate Time-Series Forecasting. In 2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI) . IEEE, 982–989
Peiwang Tang and Xianchao Zhang. 2022 · 2022
Earlier work this paper cites.
Robust time series analysis and applications: An industrial perspective. In 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 4836–4837
Qingsong Wen, Linxiao Yang, Tian Zhou, and Liang Sun. 2022 · 2022
Earlier work this paper cites.
Timesnet: Temporal 2d-variation modeling for general time series analysis. In The eleventh international conference on learning representations
Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, and Mingsheng Long. 2022 · 2022
Earlier work this paper cites.
PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting
Hao Xue and Flora D Salim. 2022 · 2022
Earlier work this paper cites.
Leveraging language foundation models for human mobility forecasting. In the 30th International Conference on Advances in Geographic Information Systems . 1–9
Hao Xue, Bhanu Prakash Voutharoja, and Flora D Salim. 2022 · 2022
Earlier work this paper cites.
A large language model for electronic health records
Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Anthony B Costa, Mona G Flores, et al · 2022
Earlier work this paper cites.
Ts2vec: Towards universal representation of time series. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 8980–8987
Zhihan Yue, Yujing Wang, Juanyong Duan, Tianmeng Yang, Congrui Huang, Yunhai Tong, and Bixiong Xu. 2022 · 2022
Earlier work this paper cites.
Fedformer: Frequency enhanced decomposed transformer for long-term series forecasting. In International conference on machine learning . 27268–27286
Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, and Rong Jin. 2022 · 2022
Earlier work this paper cites.
Foundational Models Defining a New Era in Vision: A Survey and Outlook
Muhammad Awais, Muzammal Naseer, Salman Khan, Rao Muhammad Anwer, Hisham Cholakkal, Mubarak Shah, Ming-Hsuan Yang, and Fahad Shahbaz Khan. 2023 · 2023
Earlier work this paper cites.
Accurate medium-range global weather forecasting with 3D neural networks
Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, and Qi Tian. 2023a · 2023
Earlier work this paper cites.
Accurate medium-range global weather forecasting with 3D neural networks
Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, and Qi Tian. 2023b · 2023
Cited alongside, same era.
DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
Salva Rühling Cachay, Bo Zhao, Hailey James, and Rose Yu. 2023 · 2023
Cited alongside, same era.
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
Defu Cao, Furong Jia, Sercan O Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, and Yan Liu. 2023 · 2023
Cited alongside, same era.
LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs
Ching Chang, Wen-Chih Peng, and Tien-Fu Chen. 2023a · 2023
Cited alongside, same era.
Contrastive Trajectory Similarity Learning with Dual-Feature Attention. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) . IEEE, 2933–2945
DiffLoad: uncertainty quantification in load forecasting with diffusion model
Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, and Yi Wang. 2023d · 2023
Later among the works it cites.
Leveraging vision-language models for granular market change prediction
Christopher Wimmer and Navid Rekabsaz. 2023 · 2023
Later among the works it cites.
Qianqian Xie, Weiguang Han, Yanzhao Lai, Min Peng, and Jimin Huang. 2023 · 2023
Later among the works it cites.
Temporal Data Meets LLM–Explainable Financial Time Series Forecasting
Xinli Yu, Zheng Chen, Yuan Ling, Shujing Dong, Zongyi Liu, and Yanbin Lu. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, and Egemen Tanin. 2023b · 2023
Cited alongside, same era.
FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead
Kang Chen, Tao Han, Junchao Gong, Lei Bai, Fenghua Ling, Jing-Jia Luo, Xi Chen, Leiming Ma, Tianning Zhang, Rui Su, et al · 2023
Cited alongside, same era.
Spatial-temporal Prompt Learning for Federated Weather Forecasting
Shengchao Chen, Guodong Long, Tao Shen, Tianyi Zhou, and Jing Jiang. 2023c · 2023
Cited alongside, same era.
Yakun Chen, Xianzhi Wang, and Guandong Xu. 2023e · 2023
Cited alongside, same era.
ChatGPT Informed Graph Neural Network for Stock Movement Prediction
Zihan Chen, Lei Nico Zheng, Cheng Lu, Jialu Yuan, and Di Zhu. 2023f · 2023
Cited alongside, same era.
A decoder-only foundation model for time-series forecasting
Abhimanyu Das, Weihao Kong, Rajat Sen, and Yichen Zhou. 2023 · 2023
Cited alongside, same era.
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, and Mingsheng Long. 2023 · 2023
Cited alongside, same era.
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam. 2023 · 2023
Cited alongside, same era.
Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, and Yong Li. 2023 · 2023
Later among the works it cites.
Imputation as Inpainting: Diffusion models for SpatioTemporal Data Imputation
Taeyoung Yun, Haewon Jung, and Jiwoo Son. 2023 · 2023
Later among the works it cites.
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, et al · 2023
Later among the works it cites.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
Later among the works it cites.
One Fits All: Power General Time Series Analysis by Pretrained LM
Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, and Rong Jin. 2023b · 2023
Later among the works it cites.
Energy forecasting with robust, flexible, and explainable machine learning algorithms
Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Xinyue Gu, et al · 2023
Later among the works it cites.
Chronos: Learning the Language of Time Series
Abdul Fatir Ansari, Lorenzo Stella, Caner Turkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Syndar Rangapuram, Sebastian Pineda Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, and Yuyang Wang. 2024 · 2024
Closest in time.
Video generation models as world simulators
Tim Brooks, Bill Peebles, Connor Holmes, Will DePue, Yufei Guo, Li Jing, David Schnurr, Joe Taylor, Troy Luhman, Eric Luhman, Clarence Ng, Ricky Wang, and Aditya Ramesh. 2024 · 2024
Closest in time.
NuwaTS: Mending Every Incomplete Time Series
Jinguo Cheng, Chunwei Yang, Wanlin Cai, Yuxuan Liang, and Yuankai Wu. 2024 · 2024
Closest in time.
Simulating human mobility with a trajectory generation framework based on diffusion model
Chen Chu, Hengcai Zhang, Peixiao Wang, and Feng Lu. 2024 · 2024
Closest in time.
On the constrained time-series generation problem
Andrea Coletta, Sriram Gopalakrishnan, Daniel Borrajo, and Svitlana Vyetrenko. 2024 · 2024
Closest in time.
Time Series Diffusion in the Frequency Domain
Jonathan Crabbé, Nicolas Huynh, Jan Stanczuk, and Mihaela van der Schaar. 2024 · 2024
Closest in time.
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yunzhong Qiu, Li Zhang, Jianmin Wang, and Mingsheng Long. 2024 · 2024
Closest in time.
Vijay Ekambaram, Arindam Jati, Nam H Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M Gifford, and Jayant Kalagnanam. 2024 · 2024
Closest in time.
Cheng Feng, Long Huang, and Denis Krompass. 2024 · 2024
Closest in time.
UniTS: Building a Unified Time Series Model
Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, and Marinka Zitnik. 2024 · 2024
Closest in time.
RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks
Haowen Hou and F Richard Yu. 2024 · 2024
Closest in time.
Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns. In The Twelfth International Conference on Learning Representations
Hongbin Huang, Minghua Chen, and Xiao Qiao. 2024 · 2024
Closest in time.
Empowering Time Series Analysis with Large Language Models: A Survey
Yushan Jiang, Zijie Pan, Xikun Zhang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, and Dongjin Song. 2024 · 2024
Closest in time.
Position: What Can Large Language Models Tell Us about Time Series Analysis. In International Conference on Machine Learning (ICML’24)
Ming Jin, Yifan Zhang, Wei Chen, Kexin Zhang, Yuxuan Liang, Bin Yang, Jindong Wang, Shirui Pan, and Qingsong Wen. 2024 · 2024
Closest in time.
GTM: General Trajectory Modeling with Auto-regressive Generation of Feature Domains
Yan Lin, Jilin Hu, Shengnan Guo, Bin Yang, Christian S. Jensen, Youfang Lin, and Huaiyu Wan. 2024 · 2024
Closest in time.
Spatial-temporal large language model for traffic prediction
Chenxi Liu, Sun Yang, Qianxiong Xu, Zhishuai Li, Cheng Long, Ziyue Li, and Rui Zhao. 2024c · 2024
Closest in time.
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, and Mingsheng Long. 2024b · 2024
Closest in time.
Timer: Transformers for Time Series Analysis at Scale
Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang, and Mingsheng Long. 2024d · 2024
Closest in time.
A Survey of Deep Learning and Foundation Models for Time Series Forecasting
John A. Miller, Mohammed Aldosari, Farah Saeed, Nasid Habib Barna, Subas Rana, I. Budak Arpinar, and Ninghao Liu. 2024 · 2024
Closest in time.
TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models
Yilong Ren, Yue Chen, Shuai Liu, Boyue Wang, Haiyang Yu, and Zhiyong Cui. 2024 · 2024
Closest in time.
Deep Learning for Multivariate Time Series Imputation: A Survey
Jun Wang, Wenjie Du, Wei Cao, Keli Zhang, Wenjia Wang, Yuxuan Liang, and Qingsong Wen. 2024a · 2024
Closest in time.
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Yong Liu, Yunzhong Qiu, Haoran Zhang, Jianmin Wang, and Mingsheng Long. 2024b · 2024
Closest in time.
Unified training of universal time series forecasting transformers
Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, and Doyen Sahoo. 2024 · 2024
Closest in time.
Deciphering spatio-temporal graph forecasting: A causal lens and treatment
Yutong Xia, Yuxuan Liang, Haomin Wen, Xu Liu, Kun Wang, Zhengyang Zhou, and Roger Zimmermann. 2024 · 2024
Closest in time.
UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction
Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, and Yong Li. 2024 · 2024
Closest in time.
Large Language Models for Time Series: A Survey
Xiyuan Zhang, Ranak Roy Chowdhury, Rajesh K. Gupta, and Jingbo Shang. 2024 · 2024
Closest in time.
Difftraj: Generating gps trajectory with diffusion probabilistic model
Yuanshao Zhu, Yongchao Ye, Shiyao Zhang, Xiangyu Zhao, and James Yu. 2024 · 2024
Closest in time.