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 1521–1530 of 6748 papers

Title	Date	Tasks	Status
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction	Nov 15, 2022	Graph EmbeddingPrediction	CodeCode Available
Multi-VQG: Generating Engaging Questions for Multiple Images	Nov 14, 2022	Question AnsweringQuestion Generation	CodeCode Available
Temporal patterns in insulin needs for Type 1 diabetes	Nov 14, 2022	Time SeriesTime Series Analysis	CodeCode Available
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOps	Nov 13, 2022	CPUTime Series	CodeCode Available
Similarity-based Feature Extraction for Large-scale Sparse Traffic Forecasting	Nov 13, 2022	Graph Neural NetworkTime Series	CodeCode Available
Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics	Nov 11, 2022	Time SeriesTime Series Analysis	—Unverified
Spatial Temporal Graph Convolution with Graph Structure Self-learning for Early MCI Detection	Nov 11, 2022	Self-LearningTime Series	—Unverified
Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression	Nov 11, 2022	regressionTime Series	—Unverified
Accounting for Temporal Variability in Functional Magnetic Resonance Imaging Improves Prediction of Intelligence	Nov 11, 2022	feature selectionFunctional Connectivity	CodeCode Available
Does Deep Learning REALLY Outperform Non-deep Machine Learning for Clinical Prediction on Physiological Time Series?	Nov 11, 2022	Deep LearningPrognosis	—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