id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
v405s755r2b	Xian Wu	Deep Learning for Sensory and Behavioral Time Series Analysis	2020		.txt	text/plain	216	9	21	To address this challenge, we propose three new learning architectures which capture temporal dynamics from different perspectives, including predefined resolution-aware forecasting, automated resolution-aware forecasting and customized forecasting. The key challenge in time series data is to comprehensively capture the underlying temporal pattern from sequential historical observations.	cache/v405s755r2b.txt	txt/v405s755r2b.txt