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 1541–1550 of 6748 papers

Title	Date	Tasks	Status	Score
Change point detection for graphical models in the presence of missing values	Jul 11, 2019	Change Point DetectionImputation	CodeCode Available	5
Robust and accelerated single-spike spiking neural network training with applicability to challenging temporal tasks	May 30, 2022	Audio ClassificationImage Classification	CodeCode Available	5
Estimation of Large Covariance and Precision Matrices from Temporally Dependent Observations	Dec 16, 2014	Functional ConnectivityTime Series	CodeCode Available	5
Community recovery in non-binary and temporal stochastic block models	Aug 11, 2020	Stochastic Block ModelTime Series	CodeCode Available	5
Estimating Vector Fields from Noisy Time Series	Dec 6, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise	May 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	5
Multi-Task Neural Processes	Oct 28, 2021	Time SeriesTime Series Analysis	CodeCode Available	5
Change of human mobility during COVID-19: A United States case study	Sep 18, 2021	Time Series Analysis	CodeCode Available	5
AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors	Dec 7, 2020	Feature EngineeringFeature Importance	CodeCode Available	5
Estimating optical vegetation indices and biophysical variables for temperate forests with Sentinel-1 SAR data using machine learning techniques: A case study for Czechia	Nov 13, 2023	AutoMLTime Series	CodeCode Available	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