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 811–820 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series Classification	Dec 7, 2023	Data AugmentationRepresentation Learning	CodeCode Available	1	5
SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting	Nov 16, 2022	regressionTAR	CodeCode Available	1	5
Generative time series models using Neural ODE in Variational Autoencoders	Jan 12, 2022	Time SeriesTime Series Analysis	CodeCode Available	1	5
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach	Aug 2, 2023	Anomaly DetectionDeep Learning	CodeCode Available	1	5
AtsPy: Automated Time Series Forecasting in Python	May 14, 2020	SurveyTime Series	CodeCode Available	1	5
Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting	Feb 17, 2022	Conformal PredictionPrediction Intervals	CodeCode Available	1	5
Signal Decomposition Using Masked Proximal Operators	Feb 18, 2022	Distributed OptimizationTime Series	CodeCode Available	1	5
Sig-Wasserstein GANs for Time Series Generation	Nov 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	1	5
Epicasting: An Ensemble Wavelet Neural Network (EWNet) for Forecasting Epidemics	Jun 21, 2022	SchedulingTime Series	CodeCode Available	1	5
Generative adversarial networks in time series: A survey and taxonomy	Jul 23, 2021	SurveyTime Series	CodeCode Available	1	5

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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