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 1351–1360 of 6748 papers

Title	Date	Tasks	Status
Asset Pricing with General Transaction Costs: Theory and Numerics	Apr 15, 2020	Time SeriesTime Series Analysis	—Unverified
Asset Pricing and Deep Learning	Sep 24, 2022	Deep LearningExplainable artificial intelligence	—Unverified
A CNN based method for Sub-pixel Urban Land Cover Classification using Landsat-5 TM and Resourcesat-1 LISS-IV Imagery	Dec 16, 2021	Land Cover ClassificationTime Series	—Unverified
An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series	Jul 18, 2019	Anomaly DetectionTime Series	—Unverified
Asset correlation estimation for inhomogeneous exposure pools	Sep 11, 2019	Time SeriesTime Series Analysis	—Unverified
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data	Apr 21, 2020	Deep LearningMotion Compensation	—Unverified
Assessment of electrical and infrastructure recovery in Puerto Rico following hurricane Maria using a multisource time series of satellite imagery	Jul 16, 2018	Change DetectionTime Series	—Unverified
Assessing the Potential of AI for Spatially Sensitive Nature-Related Financial Risks	Apr 26, 2024	Time Series Analysis	—Unverified
An Active Learning Framework with a Class Balancing Strategy for Time Series Classification	May 20, 2024	Active LearningClassification	—Unverified
A Bayesian Approach for Predicting Food and Beverage Sales in Staff Canteens and Restaurants	May 26, 2020	Additive modelsDemand Forecasting	—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