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 1601–1610 of 6748 papers

Title	Date	Tasks	Status
Optimal Event Monitoring through Internet Mashup over Multivariate Time Series	Oct 18, 2022	parameter estimationTime Series	—Unverified
Universal hidden monotonic trend estimation with contrastive learning	Oct 18, 2022	Contrastive LearningTime Series	—Unverified
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability	Oct 18, 2022	image-classificationImage Classification	—Unverified
Research of an optimization model for servicing a network of ATMs and information payment terminals	Oct 18, 2022	ManagementTime Series Analysis	—Unverified
Modelling Emotion Dynamics in Song Lyrics with State Space Models	Oct 17, 2022	Emotion RecognitionMusic Emotion Recognition	—Unverified
Flipped Classroom: Effective Teaching for Time Series Forecasting	Oct 17, 2022	Time SeriesTime Series Analysis	CodeCode Available
Temporal-Spatial dependencies ENhanced deep learning model (TSEN) for household leverage series forecasting	Oct 17, 2022	Time SeriesTime Series Analysis	—Unverified
tegdet: An extensible Python Library for Anomaly Detection using Time-Evolving Graphs	Oct 17, 2022	Anomaly DetectionTime Series	CodeCode Available
From time-series transcriptomics to gene regulatory networks: a review on inference methods	Oct 16, 2022	Time SeriesTime Series Analysis	—Unverified
Extreme-Long-short Term Memory for Time-series Prediction	Oct 15, 2022	EEGElectroencephalogram (EEG)	—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