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 2321–2330 of 6748 papers

Title	Date	Tasks	Status
A complex network approach to time series analysis with application in diagnosis of neuromuscular disorders	Aug 16, 2021	Electromyography (EMG)Time Series	—Unverified
Quantile Convolutional Neural Networks for Value at Risk Forecasting	Aug 21, 2019	Time SeriesTime Series Analysis	—Unverified
Inferring Global Dynamics of a Black-Box System Using Machine Learning	May 10, 2019	BIG-bench Machine LearningTime Series	—Unverified
Forecasting Drought Using Multilayer Perceptron Artificial Neural Network Model	Apr 17, 2019	Decision MakingManagement	—Unverified
Deep Learning for Energy Time-Series Analysis and Forecasting	Jun 15, 2023	Deep LearningDemand Forecasting	—Unverified
Deep Learning for Energy Markets	Aug 16, 2018	Deep LearningTime Series	—Unverified
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks	Jul 12, 2019	Anomaly DetectionTime Series	—Unverified
Deep Learning Enables Reduced Gadolinium Dose for Contrast-Enhanced Blood-Brain Barrier Opening	Jan 18, 2023	Time SeriesTime Series Analysis	—Unverified
Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network	Sep 6, 2019	Feature Engineeringfeature selection	—Unverified
An End-to-End Model for Time Series Classification In the Presence of Missing Values	Aug 11, 2024	ClassificationImputation	—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