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 1711–1720 of 6748 papers

Title	Date	Tasks	Status
Deep Canonically Correlated LSTMs	Jan 16, 2018	Time SeriesTime Series Analysis	—Unverified
Deep Canonical Time Warping	Jun 1, 2016	Time SeriesTime Series Analysis	—Unverified
Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data with Spatial Information	Jan 12, 2021	EEGElectroencephalogram (EEG)	—Unverified
Deep CHORES: Estimating Hallmark Measures of Physical Activity Using Deep Learning	Jul 26, 2020	Deep LearningTime Series	—Unverified
Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis	Aug 30, 2018	ClusteringDiagnostic	—Unverified
Deep Classification of Epileptic Signals	Jan 11, 2018	ClassificationEEG	—Unverified
Deep Reinforcement Learning for Trading	Nov 22, 2019	Deep Reinforcement Learningreinforcement-learning	—Unverified
A review on outlier/anomaly detection in time series data	Feb 11, 2020	Anomaly DetectionOutlier Detection	—Unverified
Deep Convolutional Architectures for Extrapolative Forecast in Time-dependent Flow Problems	Sep 18, 2022	Time SeriesTime Series Analysis	—Unverified
Composite FORCE learning of chaotic echo state networks for time-series prediction	Jul 6, 2022	Time SeriesTime Series Analysis	—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