[TSF] A Comprehensive Survey of Deep Learning for Time Series Forecasting: Architectural Diversity and Open Challenges
时序预测2025综述 A Comprehensive Survey of Deep Learning for … 阅读更多
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[TSF] LTSF-Linear (Are Transformers Effective for Time Series Forecasting?)
本文提出了DLinear，其通道独立策略启发了PatchTST的patch-patch注意力机制。 Are T … 阅读更多
[TSF] iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
Transformer系列时序预测改进模型——iTransformer iTransformer: Inver … 阅读更多
[TSF] PatchTST (A Time Series is Worth 64 Words: Long-term Forecasting with Transformers)
Transformer系列时序预测改进模型——PatchTST A Time Series is Worth … 阅读更多
[TSF] Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
Transformer系列时序预测改进模型——Autoformer Autoformer: Decomposi … 阅读更多
[LLM] [TSF] 原版Transformer (Attention Is All You Need)
Vanilla Transformer Attention Is All You Need（2017） 相关内 … 阅读更多
时间序列预测任务简介
时间序列预测（Time Series Prediction）常见任务简介 1 时序预测的基本概念 以IoT场景 … 阅读更多