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• Green Driver: AI in a Microcosm

  Jim Apple, Paul Chang, Aran Clauson, Heidi Dixon, Hiba Fakhoury, Matthew Ginsberg, Erin Keenan, Alex Leighton, Kevin Scavezze, Bryan Smith

  1311-1316

  2011-08-04

• Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting

  Ziyu Zhou, Yiming Huang, Yanyun Wang, Yuankai Wu, James Kwok, Yuxuan Liang

  29115-29123

  2026-03-14

• PrimeNet: Pre-training for Irregular Multivariate Time Series

  Ranak Roy Chowdhury, Jiacheng Li, Xiyuan Zhang, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang

  7184-7192

  2023-06-26

• Latent Diffusion Transformer for Probabilistic Time Series Forecasting

  Shibo Feng, Chunyan Miao, Zhong Zhang, Peilin Zhao

  11979-11987

  2024-03-24

• HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting

  Feng Shibo, Peilin Zhao, Liu Liu, Pengcheng Wu, Zhiqi Shen

  746-754

  2025-04-11

• MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting

  Wanlin Cai, Yuxuan Liang, Xianggen Liu, Jianshuai Feng, Yuankai Wu

  11141-11149

  2024-03-24

• Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting

  Nam Nguyen, Brian Quanz

  9117-9125

  2021-05-18

• WaveForM: Graph Enhanced Wavelet Learning for Long Sequence Forecasting of Multivariate Time Series

  Fuhao Yang, Xin Li, Min Wang, Hongyu Zang, Wei Pang, Mingzhong Wang

  10754-10761

  2023-06-26

• Optimizing Multivariate Performance Measures from Multi-View Data

  Jim Jing-Yan Wang, Ivor Tsang, Xin Gao

  2016-03-02

• Learning Dynamic Temporal Relations with Continuous Graph for Multivariate Time Series Forecasting (Student Abstract)

  Zhiyuan Wang, Fan Zhou, Goce Trajcevski, Kunpeng Zhang, Ting Zhong

  16358-16359

  2024-07-15

• AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data

  Santosh Palaskar, Vijay Ekambaram, Arindam Jati, Neelamadhav Gantayat, Avirup Saha, Seema Nagar, Nam H. Nguyen, Pankaj Dayama, Renuka Sindhgatta, Prateeti Mohapatra, Harshit Kumar, Jayant Kalagnanam, Nandyala Hemachandra, Narayan Rangaraj

  22962-22968

  2024-03-24

• Learnable Matrix Profile for Motif Discovery on Multivariate Time Series

  Mingkai Lin, Yinke Wang, Xiaobin Hong, Wenzhong Li

  15252-15260

  2026-03-14

• TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment

  Chenxi Liu, Qianxiong Xu, Hao Miao, Sun Yang, Lingzheng Zhang, Cheng Long, Ziyue Li, Rui Zhao

  18780-18788

  2025-04-11

• Rethinking Irregular Time Series Forecasting: A Simple Yet Effective Baseline

  Xvyuan Liu, Xiangfei Qiu, Xingjian Wu, Zhengyu Li, Chenjuan Guo, Jilin Hu, Bin Yang

  23873-23881

  2026-03-14

• GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting

  Furong Jia, Kevin Wang, Yixiang Zheng, Defu Cao, Yan Liu

  23343-23351

  2024-03-24

• Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data

  Zitao Liu, Milos Hauskrecht

  2016-02-21

• TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting

  Chuanru Ren, Yao Lu, Tianjin Huang, Haowen Zheng, Hengde Zhu, Yunyin Li, Hengxiao Li, Lu Liu

  25108-25116

  2026-03-14

• Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders

  Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu

  6897-6905

  2023-06-26

• Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting

  Muyao Wang, Wenchao Chen, Bo Chen

  15563-15570

  2024-03-24

• CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting

  Hui He, Qi Zhang, Simeng Bai, Kun Yi, Zhendong Niu

  4030-4038

  2022-06-28

• SLOTH: Structured Learning and Task-Based Optimization for Time Series Forecasting on Hierarchies

  Fan Zhou, Chen Pan, Lintao Ma, Yu Liu, Shiyu Wang, James Zhang, Xinxin Zhu, Xuanwei Hu, Yunhua Hu, Yangfei Zheng, Lei Lei, Hu Yun

  11417-11425

  2023-06-26

• Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series

  George Montanez, Saeed Amizadeh, Nikolay Laptev

  2015-02-18

• Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting

  Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

  19651-19658

  2025-04-11

• Secure and Automated Enterprise Revenue Forecasting

  Jocelyn Barker, Amita Gajewar, Konstantin Golyaev, Gagan Bansal, Matt Conners

  2018-04-27

• TapNet: Multivariate Time Series Classification with Attentional Prototypical Network

  Xuchao Zhang, Yifeng Gao, Jessica Lin, Chang-Tien Lu

  6845-6852

  2020-04-03