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 831–840 of 6748 papers

Title	Date	Tasks	Status	Hype
DYNOTEARS: Structure Learning from Time-Series Data	Feb 2, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis	Feb 1, 2020	Causal InferenceDynamic Time Warping	CodeCode Available	1
Bayesian Neural Architecture Search using A Training-Free Performance Metric	Jan 29, 2020	Bayesian OptimizationNeural Architecture Search	CodeCode Available	1
Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case	Jan 23, 2020	BIG-bench Machine LearningTime Series	CodeCode Available	1
Generalization of Change-Point Detection in Time Series Data Based on Direct Density Ratio Estimation	Jan 17, 2020	Binary ClassificationChange Point Detection	CodeCode Available	1
Mind the gap: an experimental evaluation of imputation of missing values techniques in time series	Jan 15, 2020	ImputationMissing Values	CodeCode Available	1
Explainable Deep Convolutional Candlestick Learner	Jan 8, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Discovering Nonlinear Relations with Minimum Predictive Information Regularization	Jan 7, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Root Cause Detection Among Anomalous Time Series Using Temporal State Alignment	Jan 4, 2020	Anomaly DetectionTime Series	CodeCode Available	1
Source Model Selection for Deep Learning in the Time Series Domain	Jan 3, 2020	Model SelectionTime 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