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 191–200 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
An Accurate and Fully-Automated Ensemble Model for Weekly Time Series Forecasting	Oct 16, 2020	Meta-Learningregression	CodeCode Available	1	5
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series	Jul 5, 2017	ClassificationEEG	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
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
Construe: a software solution for the explanation-based interpretation of time series	Mar 17, 2020	Atrial Fibrillation DetectionHeartbeat Classification	CodeCode Available	1	5
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19	Mar 8, 2022	Correlated Time Series ForecastingCOVID-19 Modelling	CodeCode Available	1	5
An Open Source and Reproducible Implementation of LSTM and GRU Networks for Time Series Forecasting	Jun 22, 2022	Time SeriesTime Series Analysis	CodeCode Available	1	5
Convolutional Radio Modulation Recognition Networks	Feb 12, 2016	General ClassificationTime 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

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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