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 3621–3630 of 6748 papers

Title	Date	Tasks	Status
Sufficient Forecasting Using Factor Models	May 27, 2015	Dimensionality Reductionregression	—Unverified
Summary Markov Models for Event Sequences	May 6, 2022	Time SeriesTime Series Analysis	—Unverified
SummerTime: Variable-length Time SeriesSummarization with Applications to PhysicalActivity Analysis	Feb 20, 2020	General Classificationregression	—Unverified
Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory	Jun 11, 2020	BIG-bench Machine LearningGeneral Classification	—Unverified
SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems	Nov 9, 2020	Time SeriesTime Series Analysis	—Unverified
Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms	Sep 9, 2019	BIG-bench Machine LearningEnsemble Learning	—Unverified
Supervised classification-based stock prediction and portfolio optimization	Jun 3, 2014	ClassificationGeneral Classification	—Unverified
Supervised DKRC with Images for Offline System Identification	Sep 6, 2021	Time SeriesTime Series Analysis	—Unverified
Supervised Feature Subset Selection and Feature Ranking for Multivariate Time Series without Feature Extraction	May 1, 2020	feature selectionTime Series	—Unverified
Supervised Hyperalignment for multi-subject fMRI data alignment	Jan 9, 2020	Multi-Subject Fmri Data AlignmentTime Series	—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