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 781–790 of 6748 papers

Title	Date	Tasks	Status	Hype
Machine Learning-Based Unbalance Detection of a Rotating Shaft Using Vibration Data	May 26, 2020	BIG-bench Machine LearningDiagnostic	CodeCode Available	1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks	May 24, 2020	Graph LearningGraph Neural Network	CodeCode Available	1
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data	May 22, 2020	Domain AdaptationTime Series	CodeCode Available	1
Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network	May 20, 2020	Generative Adversarial NetworkSuper-Resolution	CodeCode Available	1
Neural Controlled Differential Equations for Irregular Time Series	May 18, 2020	Irregular Time SeriesTime Series	CodeCode Available	1
DEFM: Delay E mbedding based Forecast Machine for Time Series Forecasting by Spatiotemporal Information Transformation	May 16, 2020	Time SeriesTime Series Analysis	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
RED: Deep Recurrent Neural Networks for Sleep EEG Event Detection	May 15, 2020	EEGElectroencephalogram (EEG)	CodeCode Available	1
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation	May 14, 2020	General ClassificationSpecificity	CodeCode Available	1
AtsPy: Automated Time Series Forecasting in Python	May 14, 2020	SurveyTime Series	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