BriefGPT.xyz
Nov, 2020
用表格转换器对多元时间序列进行建模
Tabular Transformers for Modeling Multivariate Time Series
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Inkit Padhi, Yair Schiff, Igor Melnyk, Mattia Rigotti, Youssef Mroueh...
TL;DR
本研究利用深度学习算法构建神经网络模型,对具有层级结构的表格时间序列进行表示学习,提供了一种类似于BERT的预训练模型以及类似于GPT的合成模型,并在信用卡诈骗检测和空气污染浓度预测两个领域应用验证了模型的效果。
Abstract
tabular datasets
are ubiquitous in data science applications. Given their importance, it seems natural to apply state-of-the-art
deep learning algorithms
in order to fully unlock their potential. Here we propose
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