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 3491–3500 of 6748 papers

Title	Date	Tasks	Status
Sparse Principal Component Analysis for High Dimensional Vector Autoregressive Models	Jun 30, 2013	Time SeriesTime Series Analysis	—Unverified
Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory	Jan 19, 2013	Computational EfficiencyTime Series Analysis	—Unverified
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting	Feb 8, 2024	Computational EfficiencyMultivariate Time Series Forecasting	—Unverified
Sparsification and Filtering for Spatial-temporal GNN in Multivariate Time-series	Mar 8, 2022	Graph Neural NetworkTime Series	—Unverified
Sparsification of the Alignment Path Search Space in Dynamic Time Warping	Nov 13, 2017	Dynamic Time WarpingGeneral Classification	—Unverified
Sparsifying Networks via Subdifferential Inclusion	Jan 1, 2021	image-classificationImage Classification	—Unverified
Sparsistent Estimation of Time-Varying Discrete Markov Random Fields	Jul 14, 2009	regressionTime Series	—Unverified
Sparsity-based Correction of Exponential Artifacts	Sep 24, 2015	EEGElectroencephalogram (EEG)	—Unverified
Spatial heterogeneity analyses identify limitations of epidemic alert systems: Monitoring influenza-like illness in France	Mar 29, 2018	EpidemiologyTime Series	—Unverified
Spatially Encoding Temporal Correlations to Classify Temporal Data Using Convolutional Neural Networks	Sep 24, 2015	ClassificationGeneral Classification	—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