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 4161–4170 of 6748 papers

Title	Date	Tasks	Status
Using Connectome Features to Constrain Echo State Networks	Jun 5, 2022	ClusteringPrediction	—Unverified
Using Deep Learning for price prediction by exploiting stationary limit order book features	Oct 23, 2018	Time SeriesTime Series Analysis	—Unverified
Using Deep Learning to Correlate Reddit Posts with Economic Time Series During the COVID-19 Pandemic	Aug 1, 2021	Time SeriesTime Series Analysis	—Unverified
Using deep neural networks to improve the precision of fast-sampled particle timing detectors	Dec 10, 2023	Time SeriesTime Series Analysis	—Unverified
Using Detailed Access Trajectories for Learning Behavior Analysis	Dec 14, 2018	Time SeriesTime Series Analysis	—Unverified
Using Entropy Measures for Monitoring the Evolution of Activity Patterns	Oct 4, 2022	Time Series Analysis	—Unverified
Using LSTM recurrent neural networks for monitoring the LHC superconducting magnets	Nov 18, 2016	Time SeriesTime Series Analysis	—Unverified
Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems	Jul 1, 2022	Hyperparameter OptimizationTime Series Analysis	—Unverified
Using Machine Learning to Assess Short Term Causal Dependence and Infer Network Links	Dec 5, 2019	BIG-bench Machine LearningCausal Inference	—Unverified
Using Machine Learning to Predict Realized Variance	Sep 22, 2019	BIG-bench Machine Learningregression	—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