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 3121–3130 of 6748 papers

Title	Date	Tasks	Status
Fractal structures in Adversarial Prediction	Apr 29, 2013	PredictionTime Series	—Unverified
Human Activity Recognition using Smartphone	Jan 30, 2014	Active LearningActivity Recognition	—Unverified
Fractal approach towards power-law coherency to measure cross-correlations between time series	Feb 24, 2017	Time SeriesTime Series Analysis	—Unverified
ARISE: ApeRIodic SEmi-parametric Process for Efficient Markets without Periodogram and Gaussianity Assumptions	Nov 8, 2021	BIG-bench Machine LearningTime Series	—Unverified
Human-like Time Series Summaries via Trend Utility Estimation	Jan 16, 2020	Time SeriesTime Series Analysis	—Unverified
Human Motion Prediction via Pattern Completion in Latent Representation Space	Apr 18, 2019	Action ClassificationGeneral Classification	—Unverified
Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems	Apr 13, 2020	Anomaly DetectionDecision Making	—Unverified
Hybrid Backpropagation Parallel Reservoir Networks	Oct 27, 2020	EEGElectroencephalogram (EEG)	—Unverified
Hybrid Cryptocurrency Pump and Dump Detection	Mar 14, 2020	Anomaly DetectionTime Series	—Unverified
Fractal analyses of networks of integrate-and-fire stochastic spiking neurons	Jan 19, 2018	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