标题:Long-term Forecasting with TiDE: Time-series Dense Encoder 链接:arxiv.org/abs/2304.0842 一、模型介绍 1.1 前言 最近的工作表明,在长期时间序列预测中,简单的线性模型可以优于几种基于Transformer的方法。受此启发,文章提出了一种基于多层感知器(MLP)的编码器-解码器模型,即时间
TiDE整体架构 TiDE模型整体架构如上图。首先,它也是和PatchTST一样,假设通道独立的。也就是说将多变量预测转变为多个单变量预测,模型参数共享。通道独立的详细介绍可见: 其次,和PatchTST以及一些基于MLP的预测模型相比,它不仅利用了过去的序列值(LookBack),而且利用了一些协变量信息,比如静态协变量(Attributes)和在任...
Long-term Forecasting with TiDE: Time-series Dense Encoder 论文地址:https://arxiv.org/abs/2304.08424 代码地址:https://github.com/google-research/google-research/tree/master/tide 摘要:这篇论文提出了时间序列密集编码器(TiDE),一种基于MLP的编码器-解码器模型,用于长期时间序列预测,它具有线性模型的简单...
Google团队在2023年的时间序列分析领域推出了新模型——Long-term Forecasting with TiDE: Time-series Dense Encoder。该模型以多层感知器（MLP）为基础，旨在解决长期时间序列预测中的复杂问题，如非线性依赖和外部变量处理。TiDE在保持线性模型的简单性和速度的同时，性能上能与基于Transformer的方法相媲美，...
An implementation of (Google)Long-term Time Series Forecasting with TiDE: Time-series Dense Encoder - Helloworld2345567/Google_TiDE_implementation
Long-short range time series forecasting is essential for predicting future trends and patterns over extended periods. While deep learning models such as Transformers have made significant strides in advancing time series forecasting, they often encounter difficulties in capturing long-term dependencies and...
Long-term Forecasting with TiDE: Time-series Dense Encoder 4 code implementations • 17 Apr 2023 Recent work has shown that simple linear models can outperform several Transformer based approaches in long term time-series forecasting. Ranked #7 on Time Series Forecasting on ETTh2 (96) ...
tide gauge and, more recently, satellite altimetry data. Using a three-dimensional global ocean model, we estimate that strengthening of stratification between 1993 and 2020 caused open-ocean trends of order 0.1 mm yr−1in the barotropic M2tide, similar in structure and magnitude to long-term ...
论文标题:TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting (这篇的标题应该是在模仿PatchTST的标题:A time series is worth 64 words: Long-term forecasting with transformers) 作者: Md Atik Ahamed, Qiang Cheng 机构:肯塔基大学(UKY) 论文链接:arxiv.org/abs/2403.0989 Cool Paper...
The current long-term decline in CSL is expected to continue into the foreseeable future, under global warming scenarios. Key Points PER flux-reconstructed Caspian Sea level change agrees remarkably well with tide gauge and satellite measurements Increased evaporation rates over the Caspian Sea play a...