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 821–830 of 6748 papers

Title	Date	Tasks	Status	Hype
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values	Feb 21, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity Detection	Feb 21, 2020	Anomaly DetectionClustering	CodeCode Available	1
Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network	Feb 20, 2020	Time Series Analysis	CodeCode Available	1
Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning Techniques	Feb 19, 2020	regressionTime Series	CodeCode Available	1
Deep reconstruction of strange attractors from time series	Feb 14, 2020	Dimensionality ReductionTime Series	CodeCode Available	1
ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting	Feb 11, 2020	Deep LearningTime Series	CodeCode Available	1
Selecting time-series hyperparameters with the artificial jackknife	Feb 11, 2020	Missing ValuesTime Series	CodeCode Available	1
A Physiology-Driven Computational Model for Post-Cardiac Arrest Outcome Prediction	Feb 9, 2020	ICU AdmissionTime Series Analysis	CodeCode Available	1
Improving S&P stock prediction with time series stock similarity	Feb 8, 2020	PredictionStock Market Prediction	CodeCode Available	1
Meta-learning framework with applications to zero-shot time-series forecasting	Feb 7, 2020	Meta-LearningTime Series	CodeCode Available	1

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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