论文标题
时间序列分析中的变压器：教程
Transformers in Time-series Analysis: A Tutorial
论文作者
论文摘要
变压器架构具有广泛的应用程序，尤其是在自然语言处理和计算机视觉方面。最近，变形金刚用于时间序列分析的各个方面。本教程概述了变压器体系结构，其应用程序以及最新时间序列分析研究论文的示例集。我们深入研究了变压器的核心组成部分的解释，包括自我发项机制，位置编码，多头和编码器/解码器。对初始变压器体系结构的几种增强功能将突出显示，以解决时间序列任务。该教程还提供了最佳实践和技术，以克服有效训练变压器进行时间序列分析的挑战。
Transformer architecture has widespread applications, particularly in Natural Language Processing and computer vision. Recently Transformers have been employed in various aspects of time-series analysis. This tutorial provides an overview of the Transformer architecture, its applications, and a collection of examples from recent research papers in time-series analysis. We delve into an explanation of the core components of the Transformer, including the self-attention mechanism, positional encoding, multi-head, and encoder/decoder. Several enhancements to the initial, Transformer architecture are highlighted to tackle time-series tasks. The tutorial also provides best practices and techniques to overcome the challenge of effectively training Transformers for time-series analysis.
