Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect

22 July 2022

Papers citing "Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect"

5 / 5 papers shown

Title
FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series Forecasting Li Shen Yuning Wei Yangzhu Wang Huaxin Qiu OOD AI4TS 13 7 0 19 Jun 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
Yformer: U-Net Inspired Transformer Architecture for Far Horizon Time Series Forecasting Kiran Madhusudhanan Johannes Burchert Nghia Duong-Trung Stefan Born Lars Schmidt-Thieme AI4TS AI4CE 41 21 0 13 Oct 2021
ResNet strikes back: An improved training procedure in timm Ross Wightman Hugo Touvron Hervé Jégou AI4TS 212 487 0 01 Oct 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