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 271–280 of 6748 papers

Title	Date	Tasks	Status	Hype
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks	Jan 6, 2022	Audio ClassificationClassification	CodeCode Available	1
CKConv: Continuous Kernel Convolution For Sequential Data	Feb 4, 2021	Permuted-MNISTSequential Image Classification	CodeCode Available	1
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks	Feb 16, 2021	BIG-bench Machine LearningGraph Neural Network	CodeCode Available	1
ClaSP -- Parameter-free Time Series Segmentation	Jul 28, 2022	Change Point DetectionSegmentation	CodeCode Available	1
ClaSP - Time Series Segmentation	Oct 26, 2021	Change Point DetectionSegmentation	CodeCode Available	1
Closed-Form Diffeomorphic Transformations for Time Series Alignment	Jun 16, 2022	CPUForm	CodeCode Available	1
Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation	Aug 21, 2020	Change Point DetectionTime Series	CodeCode Available	1
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
Changing Fashion Cultures	Mar 23, 2017	Cultural Vocal Bursts Intensity PredictionTime Series	CodeCode Available	1
Causal Forecasting:Generalization Bounds for Autoregressive Models	Nov 18, 2021	Learning TheoryTime 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