Ti-MAE: Self-Supervised Masked Time Series Autoencoders

Ti-MAE: Self-Supervised Masked Time Series Autoencoders

21 January 2023

Papers citing "Ti-MAE: Self-Supervised Masked Time Series Autoencoders"

9 / 9 papers shown

Title
Towards Generalisable Time Series Understanding Across Domains Özgün Turgut Philip Muller M. Menten Daniel Rueckert AI4TS 51 1 0 09 Oct 2024
Unsupervised Multi-modal Feature Alignment for Time Series Representation Learning Cheng Liang Donghua Yang Zhiyu Liang Hongzhi Wang Zheng Liang Xiyang Zhang Jianfeng Huang AI4TS 185 1 0 09 Dec 2023
Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools Wentao Zhang Yilei Zhao Shuo Sun Jie Ying Yonggang Xie Zitao Song Xinrun Wang Bo An AIFin OOD 21 5 0 17 Nov 2023
A Unified Masked Autoencoder with Patchified Skeletons for Motion Synthesis Esteve Valls Mascaro Hyemin Ahn Dongheui Lee CVBM 37 4 0 14 Aug 2023
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping Zhe Li Shiyi Qi Yiduo Li Zenglin Xu AI4TS 23 103 0 18 May 2023
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling Jiaxiang Dong Haixu Wu Haoran Zhang Li Zhang Jianmin Wang Mingsheng Long AI4TS 31 82 0 02 Feb 2023
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar Steven C. H. Hoi AI4TS 117 394 0 03 Feb 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 314 7,457 0 11 Nov 2021
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou Shanghang Zhang J. Peng Shuai Zhang Jianxin Li Hui Xiong Wan Zhang AI4TS 169 3,900 0 14 Dec 2020