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 931–940 of 6748 papers

Title	Date	Tasks	Status
Calibration of Machine Learning Classifiers for Probability of Default Modelling	Oct 24, 2017	BIG-bench Machine LearningBinary Classification	—Unverified
An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development	Mar 25, 2022	Neural Architecture SearchReinforcement Learning (RL)	—Unverified
Affine and Regional Dynamic Time Warpng	May 25, 2015	Dynamic Time WarpingTime Series	—Unverified
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting	Sep 25, 2020	Demand ForecastingGraph Neural Network	—Unverified
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems	Apr 5, 2020	Dimensionality ReductionTime Series Analysis	—Unverified
A Convolutional-Attentional Neural Framework for Structure-Aware Performance-Score Synchronization	Apr 19, 2022	Time SeriesTime Series Analysis	—Unverified
Calculation of Sub-bands 1,2,5,6 for 64-Point Complex FFT and Its extension to N (=2^N) Point FFT	Mar 3, 2022	Time SeriesTime Series Analysis	—Unverified
An Incremental Boolean Tensor Factorization approach to model Change Patterns of Objects in Images	Mar 23, 2018	Change DetectionGeneral Classification	—Unverified
An Improvement of PAA on Trend-Based Approximation for Time Series	Jun 28, 2019	Anomaly DetectionDimensionality Reduction	—Unverified
A Feature Selection Method for Multi-Dimension Time-Series Data	Apr 22, 2021	Activity Recognitionfeature selection	—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