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 161–170 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation	May 14, 2020	General ClassificationSpecificity	CodeCode Available	1	5
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification	Dec 9, 2020	Anomaly DetectionAtrial Fibrillation Detection	CodeCode Available	1	5
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks	Jan 6, 2022	Audio ClassificationClassification	CodeCode Available	1	5
Conditional GAN for timeseries generation	Jun 30, 2020	Generative Adversarial NetworkTime Series	CodeCode Available	1	5
An Experimental Review on Deep Learning Architectures for Time Series Forecasting	Mar 22, 2021	Deep LearningTime Series	CodeCode Available	1	5
An Evaluation of Change Point Detection Algorithms	Mar 13, 2020	Change Point DetectionTime Series	CodeCode Available	1	5
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent Autoencoders	Dec 5, 2021	Anomaly DetectionTime Series	CodeCode Available	1	5
A Neural PDE Solver with Temporal Stencil Modeling	Feb 16, 2023	Time SeriesTime Series Analysis	CodeCode Available	1	5
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series	Sep 23, 2021	Anomaly DetectionTime Series	CodeCode Available	1	5
ClaSP -- Parameter-free Time Series Segmentation	Jul 28, 2022	Change Point DetectionSegmentation	CodeCode Available	1	5

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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