Foundation Models for Time Series Analysis: A Tutorial and Survey Abstract 时间序列分析是数据挖掘社区中的焦点,是提取对无数实际应用程序至关重要的有价值见解的基石。基础模型(FM)的最新进展从根本上重塑了时间序列分析的模型设计范式,在实践中推动了各种下游任务。这些创新方法通常利用预先训练或微调的 FM 来...
Inductive Biases for Time Series Transformers Transformers and GNN for Time Series Pre-trained Transformers for Time Series 之前尝试了原始的transformer 做一些微调适配时序预测的问题,发现效果还行,但是也没有啥magic,简单来说精心设计的tfm和精心设计的LSTM,CNN 在效果上差异不是很明显.这里看看有没有啥新的思...
A survey and paper list of current Diffusion Model for Time Series and SpatioTemporal Data with awesome resources (paper, application, review, survey, etc.). - whyywh/Awesome-TimeSeries-SpatioTemporal-Diffusion-Model
Diffusion Model for Time Series and Spatio-Temporal Data A curated list of Diffusion Models for Time Series, SpatioTemporal Data and Tabular Data with awesome resources (paper, code, application, review, survey, etc.), which aims to comprehensively and systematically summarize the recent advances to...
感觉很近没听到故事这么精彩的 talk 了: Ryan Williams 最近在 Simons Institute 讲述了他自本科起近二十年试图推翻 Strong Exponential-Time Hypothesis 的失败经历 -- 真的失败经历, 没有引号, 他到现在为止还是没能推翻 SETH. 他在Cornell 读本科的时候坚信 P=NP, 还被 Aaronson 在邮件里科普了 PCP 定理; ...
好了伤疤忘了痛? | In a survey conducted this week bymarket research firm Prolific, shared with the Financial Times, a quarter of a representative sample of almost 1,000 respondents said they only have “a vague memory” of how they spent their time during lockdown. ...
Robusttad: Robust time series anomaly detection via decomposition and convolutional neural networks. MileTS’20: 6th KDD Workshop on Mining and Learning from Time Series, pages 1–6, 2020.) [Lee等人,2019年]的另一项最新工作提出利用替代数据来改善深度神经网络中康复时间序列的分类性能。工作中采用了...
Time Forcasting Survey Informer: 最强最快的序列预测神器 Informer适用于具有周期性的数据以及适合较长的时序预测任务,如果预测任务的时序较短反而不能很好的体现informer应有的性能。长序列时间序列预测(LSTF)要求模型具有很高的预测能力,即能够有效地捕捉输出和输入之间精确的长期相关性依赖。
: 我们系一个小姐姐就在做female的labor market 做了个survey 瑞士对女性工作的期望(尤其是full time)比美国还低 感觉这种东西很难涨回去 司马懿: @叶赌徒 展示了一张有趣的图。从2000年左右开始,中国的女性劳动参与率在不停的下降。这件事情是好是坏呢?
Therefore, we seek your cooperation to complete the following survey form which will be active starting from 16th May 2023 until 26th May 2023.This survey aims to collect opinions and feedback from the campus community and it will take approximately 5 minutes to answer all questions.The survey ...