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 3651–3660 of 6748 papers

Title	Date	Tasks	Status
Synthesising a Database of Parameterised Linear and Non-Linear Invariants for Time-Series Constraints	Jan 15, 2019	Time SeriesTime Series Analysis	—Unverified
Synthesizing time-series wound prognosis factors from electronic medical records using generative adversarial networks	May 3, 2021	PrognosisTime Series	—Unverified
Synthetic Active Distribution System Generation via Unbalanced Graph Generative Adversarial Network	Aug 2, 2021	Generative Adversarial NetworkTime Series	—Unverified
Synthetic Control Methods and Big Data	Feb 28, 2018	counterfactualTime Series	—Unverified
Synthetic Event Time Series Health Data Generation	Nov 14, 2019	Generative Adversarial NetworkTime Series	—Unverified
Synthetic Photovoltaic and Wind Power Forecasting Data	Apr 1, 2022	Multi-Task LearningTime Series	—Unverified
Synthetic Time-Series Load Data via Conditional Generative Adversarial Networks	Jul 8, 2021	Time SeriesTime Series Analysis	—Unverified
System Identification in Multi-Actuator Hard Disk Drives with Colored Noises using Observer/Kalman Filter Identification (OKID) Framework	Sep 25, 2021	Time SeriesTime Series Analysis	—Unverified
System identification using Bayesian neural networks with nonparametric noise models	Apr 25, 2021	Time SeriesTime Series Analysis	—Unverified
T4PdM: a Deep Neural Network based on the Transformer Architecture for Fault Diagnosis of Rotating Machinery	Apr 7, 2022	Decision MakingDiagnostic	—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