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 1321–1330 of 6748 papers

Title	Date	Tasks	Status
Multidimensional dynamic factor models	Jan 29, 2023	Missing ValuesTime Series	—Unverified
Optimizing a Bayesian method for estimating the Hurst exponent in behavioral sciences	Jan 28, 2023	Computational EfficiencyTime Series	—Unverified
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network	Jan 28, 2023	Graph Neural NetworkTime Series	—Unverified
Localizing the Origin of Idiopathic Ventricular Arrhythmia from ECG Using an Attention-Based Recurrent Convolutional Neural Network	Jan 28, 2023	RhythmTime Series	—Unverified
Targeted Attacks on Timeseries Forecasting	Jan 27, 2023	Adversarial AttackTime Series	—Unverified
PrecTime: A Deep Learning Architecture for Precise Time Series Segmentation in Industrial Manufacturing Operations	Jan 27, 2023	SegmentationTime Series	—Unverified
Machine Learning Approach and Extreme Value Theory to Correlated Stochastic Time Series with Application to Tree Ring Data	Jan 27, 2023	DescriptiveTime Series	—Unverified
Effect of temporal resolution on the reproduction of chaotic dynamics via reservoir computing	Jan 27, 2023	Time SeriesTime Series Analysis	—Unverified
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective	Jan 27, 2023	FairnessMultivariate Time Series Forecasting	CodeCode Available
Learning the Dynamics of Sparsely Observed Interacting Systems	Jan 27, 2023	Time SeriesTime Series Analysis	CodeCode Available

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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