1 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
vLinear: A Powerful Linear Model for Multivariate Time Series Forecasting
Wenzhen Yue, Ruohao Guo, Ji Shi +3
In this paper, we present \textbf{vLinear}, an effective yet efficient \textbf{linear}-based multivariate time series forecaster featuring two components: the \textbf{v}ecTrans mod…
OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domain
Wenzhen Yue, Yong Liu, Haoxuan Li +5
This paper presents , a -based multivariate time series forecasting model that operates in an rthogonally transformed domain. Recent…
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting
Wenzhen Yue, Yong Liu, Xianghua Ying +3
This paper presents \textbf{FreEformer}, a simple yet effective model that leverages a \textbf{Fre}quency \textbf{E}nhanced Trans\textbf{former} for multivariate time series foreca…
Sub-Adjacent Transformer: Improving Time Series Anomaly Detection with Reconstruction Error from Sub-Adjacent Neighborhoods
Wenzhen Yue, Xianghua Ying, Ruohao Guo +5
In this paper, we present the Sub-Adjacent Transformer with a novel attention mechanism for unsupervised time series anomaly detection. Unlike previous approaches that rely on all…