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 2141–2150 of 6748 papers

Title	Date	Tasks	Status
Depth Evaluation for Metal Surface Defects by Eddy Current Testing using Deep Residual Convolutional Neural Networks	Mar 8, 2021	Time SeriesTime Series Analysis	—Unverified
Depression Diagnosis and Drug Response Prediction via Recurrent Neural Networks and Transformers Utilizing EEG Signals	Mar 9, 2023	Drug Response PredictionEEG	—Unverified
Backpropagation on Dynamical Networks	Jul 7, 2022	Time Series Analysis	—Unverified
Dependent Matérn Processes for Multivariate Time Series	Feb 11, 2015	Computational EfficiencyTime Series	—Unverified
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks	Nov 25, 2020	Time Series AnalysisTime Series Prediction	—Unverified
Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective	May 10, 2018	Density EstimationTime Series	—Unverified
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification	Jan 8, 2016	ClassificationGeneral Classification	—Unverified
Denoising Time Series Data Using Asymmetric Generative Adversarial Networks	Jun 17, 2018	DenoisingEEG	—Unverified
Denoising neural networks for magnetic resonance spectroscopy	Oct 31, 2022	Deep LearningDenoising	—Unverified
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models	Jan 10, 2020	Deep LearningElectrocardiography (ECG)	—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