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 2951–2960 of 6748 papers

Title	Date	Tasks	Status
Energy consumption forecasting using a stacked nonparametric Bayesian approach	Nov 11, 2020	Time SeriesTime Series Analysis	—Unverified
Granger Causality in Multi-variate Time Series using a Time Ordered Restricted Vector Autoregressive Model	Nov 11, 2015	EEGElectroencephalogram (EEG)	—Unverified
A Soft Computing Approach for Selecting and Combining Spectral Bands	Nov 10, 2020	ClassificationGeneral Classification	—Unverified
Granger Causal Structure Reconstruction from Heterogeneous Multivariate Time Series	Sep 25, 2019	Time SeriesTime Series Analysis	—Unverified
Granger Mediation Analysis of Multiple Time Series with an Application to fMRI	Sep 15, 2017	Time SeriesTime Series Analysis	—Unverified
Graph2Seq: Scalable Learning Dynamics for Graphs	Feb 14, 2018	Combinatorial OptimizationTime Series	—Unverified
GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection	May 23, 2022	Anomaly DetectionGraph Neural Network	—Unverified
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version	Mar 19, 2021	Correlated Time Series ForecastingGraph Attention	—Unverified
Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components	Nov 14, 2014	Causal InferenceTime Series	—Unverified
A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes	May 12, 2020	ClusteringTime Series	—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