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 2471–2480 of 6748 papers

Title	Date	Tasks	Status
Evolving Gaussian Process kernels from elementary mathematical expressions	Oct 11, 2019	Time SeriesTime Series Analysis	—Unverified
Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network Construction	Dec 23, 2015	EEGElectroencephalogram (EEG)	—Unverified
EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting	Apr 14, 2022	Time SeriesTime Series Analysis	—Unverified
Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data	Feb 17, 2018	BIG-bench Machine LearningTime Series	—Unverified
Exact Bayesian inference for off-line change-point detection in tree-structured graphical models	Mar 25, 2016	Bayesian InferenceChange Point Detection	—Unverified
Exact Indexing of Time Series under Dynamic Time Warping	Feb 11, 2020	Dynamic Time WarpingTime Series	—Unverified
Exact Mean Computation in Dynamic Time Warping Spaces	Oct 24, 2017	BenchmarkingDynamic Time Warping	—Unverified
Statistical Inference for the Dynamic Time Warping Distance, with Application to Abnormal Time-Series Detection	Feb 14, 2022	Decision MakingDynamic Time Warping	—Unverified
Exact Tests for Offline Changepoint Detection in Multichannel Binary and Count Data with Application to Networks	Aug 20, 2020	Time SeriesTime Series Analysis	—Unverified
A Novel Multi-Centroid Template Matching Algorithm and Its Application to Cough Detection	Sep 1, 2021	Dynamic Time WarpingTemplate Matching	—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