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 3731–3740 of 6748 papers

Title	Date	Tasks	Status
RNN-based Early Cyber-Attack Detection for the Tennessee Eastman Process	Sep 7, 2017	Cyber Attack DetectionFault Detection	—Unverified
Roadmap on Signal Processing for Next Generation Measurement Systems	Nov 3, 2021	Time SeriesTime Series Analysis	—Unverified
Road Surface Friction Prediction Using Long Short-Term Memory Neural Network Based on Historical Data	Nov 1, 2019	Decision MakingFriction	—Unverified
A Comprehensive Guide to CAN IDS Data & Introduction of the ROAD Dataset	Dec 29, 2020	Anomaly DetectionBenchmarking	—Unverified
Robust and efficient change point detection using novel multivariate rank-energy GoF test	Oct 29, 2021	Change Point DetectionTime Series	—Unverified
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version	Apr 7, 2022	Outlier DetectionTime Series	—Unverified
Robust and fast heart rate variability analysis of long and noisy electrocardiograms using neural networks and images	Feb 16, 2019	Heart Rate VariabilityTime Series	—Unverified
Robust and Scalable Models of Microbiome Dynamics	Jul 1, 2018	Time Series Analysis	—Unverified
Robust and Scalable Models of Microbiome Dynamics	May 11, 2018	Time Series Analysis	—Unverified
Robust Anomaly Detection for Time-series Data	Feb 6, 2022	Anomaly DetectionTime 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