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 4501–4510 of 6748 papers

Title	Date	Tasks	Status
Laplacian Convolutional Representation for Traffic Time Series Imputation	Dec 3, 2022	Decision MakingImage Inpainting	—Unverified
Large Language Models are Few-shot Multivariate Time Series Classifiers	Jan 30, 2025	Representation LearningTime Series	—Unverified
Large Language models for Time Series Analysis: Techniques, Applications, and Challenges	May 21, 2025	Time SeriesTime Series Analysis	—Unverified
Estimation of Large Financial Covariances: A Cross-Validation Approach	Dec 10, 2020	ManagementTime Series	—Unverified
Large-scale Augmented Granger Causality (lsAGC) for Connectivity Analysis in Complex Systems: From Computer Simulations to Functional MRI (fMRI)	Jan 10, 2021	Dimensionality ReductionTime Series	—Unverified
Large-scale directed network inference with multivariate transfer entropy and hierarchical statistical testing	Jul 30, 2019	EEGElectroencephalogram (EEG)	—Unverified
Large-Scale Extended Granger Causality for Classification of Marijuana Users From Functional MRI	Jan 6, 2021	Dimensionality Reductionfeature selection	—Unverified
Large-scale kernelized GRANGER causality to infer topology of directed graphs with applications to brain networks	Nov 16, 2020	Time SeriesTime Series Analysis	—Unverified
Scalable Learning in Reproducing Kernel Krein Spaces	Sep 6, 2018	Time SeriesTime Series Analysis	—Unverified
Large-scale nonlinear Granger causality: A data-driven, multivariate approach to recovering directed networks from short time-series data	Sep 10, 2020	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