Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 4131–4140 of 6748 papers

Title	Date	Tasks	Status
Unsupervised Driving Behavior Analysis using Representation Learning and Exploiting Group-based Training	May 12, 2022	Representation LearningTime Series	—Unverified
Unsupervised Driving Event Discovery Based on Vehicle CAN-data	Jan 12, 2023	Contrastive LearningSelf-Supervised Learning	—Unverified
Unsupervised Event Coreference Resolution	Jun 1, 2014	coreference-resolutionCoreference Resolution	—Unverified
Unsupervised Flood Detection on SAR Time Series	Dec 7, 2022	Change DetectionContrastive Learning	—Unverified
Unsupervised learning for economic risk evaluation in the context of Covid-19 pandemic	Nov 26, 2020	Time SeriesTime Series Analysis	—Unverified
Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition	Nov 19, 2018	ClassificationEEG	—Unverified
Unsupervised Learning through Temporal Smoothing and Entropy Maximization	May 8, 2019	Time SeriesTime Series Analysis	—Unverified
Unsupervised model-free representation learning	Apr 17, 2013	modelRepresentation Learning	—Unverified
Unsupervised non-parametric change point detection in quasi-periodic signals	Feb 7, 2020	Change Point DetectionTime Series	—Unverified
Unsupervised Online Anomaly Detection On Irregularly Sampled Or Missing Valued Time-Series Data Using LSTM Networks	May 25, 2020	Anomaly Detectionfeature selection	—Unverified

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All datasets PhysioNet Challenge 2012 Speech Commands Ventilator Pressure Prediction

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	naive classifier	F1	87.47	—	Unverified
2	GRU-D - APC (n = 1)	F1	27.3	—	Unverified
3	GRU-APC (n = 1)	F1	25.7	—	Unverified
4	GRU-D	F1	22.5	—	Unverified
5	GRU	F1	22.3	—	Unverified
6	GRU-Simple	F1	22.2	—	Unverified
7	GRU-Mean	F1	22.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SepTr	% Test Accuracy	98.51	—	Unverified
2	ViT	% Test Accuracy	98.11	—	Unverified
3	FlexTCN-4	% Test Accuracy	97.73	—	Unverified
4	MatchboxNet	% Test Accuracy	97.4	—	Unverified
5	CKCNN (100k)	% Test Accuracy	95.27	—	Unverified
6	FlexTCN-6	% Test Accuracy (Raw Data)	91.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResBiLSTM	MAE	0.13	—	Unverified