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 261–270 of 6748 papers

Title	Date	Tasks	Status	Hype
CKConv: Continuous Kernel Convolution For Sequential Data	Feb 4, 2021	Permuted-MNISTSequential Image Classification	CodeCode Available	1
ClaSP - Time Series Segmentation	Oct 26, 2021	Change Point DetectionSegmentation	CodeCode Available	1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection	Dec 17, 2020	Malware DetectionTime Series	CodeCode Available	1
Compatible deep neural network framework with financial time series data, including data preprocessor, neural network model and trading strategy	May 11, 2022	Binary ClassificationFeature Engineering	CodeCode Available	1
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series	Oct 21, 2023	Contrastive LearningEEG	CodeCode Available	1
Chaos as an interpretable benchmark for forecasting and data-driven modelling	Oct 11, 2021	BenchmarkingSymbolic Regression	CodeCode Available	1
Changing Fashion Cultures	Mar 23, 2017	Cultural Vocal Bursts Intensity PredictionTime Series	CodeCode Available	1
Data-driven discovery of intrinsic dynamics	Aug 12, 2021	Time Series Analysis	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
AA-Forecast: Anomaly-Aware Forecast for Extreme Events	Aug 21, 2022	Anomaly ForecastingMultivariate Time Series Forecasting	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