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 301–310 of 6748 papers

Title	Date	Tasks	Status	Hype
Detecting Multivariate Time Series Anomalies with Zero Known Label	Aug 3, 2022	Anomaly DetectionDensity Estimation	CodeCode Available	1
MFRFNN: Multi-Functional Recurrent Fuzzy Neural Network for Chaotic Time Series Prediction	Aug 1, 2022	PredictionStock Price Prediction	CodeCode Available	1
ClaSP -- Parameter-free Time Series Segmentation	Jul 28, 2022	Change Point DetectionSegmentation	CodeCode Available	1
A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecasting	Jul 28, 2022	Conformal PredictionDecision Making	CodeCode Available	1
Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection	Jul 25, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available	1
dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification	Jul 25, 2022	ClassificationExplainable Models	CodeCode Available	1
Benchmark time series data sets for PyTorch -- the torchtime package	Jul 25, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data	Jul 24, 2022	Anomaly DetectionAutonomous Driving	CodeCode Available	1
Respecting Time Series Properties Makes Deep Time Series Forecasting Perfect	Jul 22, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
Transfer learning for time series classification using synthetic data generation	Jul 16, 2022	Classificationregression	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