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 1771–1780 of 6748 papers

Title	Date	Tasks	Status	Score
Dynamic Natural Language Processing with Recurrence Quantification Analysis	Mar 19, 2018	Time SeriesTime Series Analysis	CodeCode Available	5
DynaConF: Dynamic Forecasting of Non-Stationary Time Series	Sep 17, 2022	Deep LearningTime Series	CodeCode Available	5
Sketches for Time-Dependent Machine Learning	Aug 26, 2021	BIG-bench Machine LearningTime Series	CodeCode Available	5
Dynamic cyber risk estimation with Competitive Quantile Autoregression	Jan 25, 2021	Time SeriesTime Series Analysis	CodeCode Available	5
Dynamic process fault prediction using canonical variable trend analysis	Apr 12, 2016	PredictionTime Series	CodeCode Available	5
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes	Oct 22, 2020	Anomaly DetectionTime Series	CodeCode Available	5
Cadence: A Practical Time-series Partitioning Algorithm for Unlabeled IoT Sensor Streams	Dec 6, 2021	Activity RecognitionChange Point Detection	CodeCode Available	5
DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting	Nov 3, 2019	Multivariate Time Series ForecastingTime Series	CodeCode Available	5
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series Analysis	Dec 1, 2024	Computational EfficiencyPhysics-informed machine learning	CodeCode Available	5
Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural Network	Nov 19, 2019	Autonomous VehiclesDriver Identification	CodeCode Available	5

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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