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 411–420 of 6748 papers

Title	Date	Tasks	Status	Hype
Adaptive Conformal Predictions for Time Series	Feb 15, 2022	Conformal PredictionDecision Making	CodeCode Available	1
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting	Dec 15, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes	Oct 15, 2021	DescriptiveImage Classification	CodeCode Available	1
catch22: CAnonical Time-series CHaracteristics	Jan 29, 2019	ClassificationClustering	CodeCode Available	1
Forecasting with Deep Learning	Feb 17, 2023	Deep LearningTime Series	CodeCode Available	1
Forecasting with sktime: Designing sktime's New Forecasting API and Applying It to Replicate and Extend the M4 Study	May 16, 2020	BIG-bench Machine LearningTime Series	CodeCode Available	1
ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting	Feb 11, 2020	Deep LearningTime Series	CodeCode Available	1
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values	Feb 21, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting	Apr 21, 2022	Decision MakingPrediction Intervals	CodeCode Available	1
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks	Feb 16, 2021	BIG-bench Machine LearningGraph Neural Network	CodeCode Available	1

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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