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 3011–3020 of 6748 papers

Title	Date	Tasks	Status
Handling Variable-Dimensional Time Series with Graph Neural Networks	Jul 1, 2020	Activity RecognitionGraph Neural Network	—Unverified
Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review	Jun 10, 2022	Time SeriesTime Series Analysis	—Unverified
Learning low-dimensional state embeddings and metastable clusters from time series data	Jun 1, 2019	ClusteringTime Series	—Unverified
Happy or grumpy? A Machine Learning Approach to Analyze the Sentiment of Airline Passengers' Tweets	Sep 28, 2022	Lexical AnalysisSentiment Analysis	—Unverified
Differential Recurrent Neural Network and its Application for Human Activity Recognition	May 9, 2019	Activity RecognitionHuman Activity Recognition	—Unverified
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes	Nov 29, 2021	Multi-Task LearningPrediction	—Unverified
From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?	May 29, 2025	Time SeriesTime Series Analysis	—Unverified
From Generalization Analysis to Optimization Designs for State Space Models	May 4, 2024	State Space ModelsTime Series	—Unverified
Concentration inequalities for correlated network-valued processes with applications to community estimation and changepoint analysis	Aug 2, 2022	Time SeriesTime Series Analysis	—Unverified
From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning	Sep 6, 2018	AstronomyBIG-bench Machine Learning	—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