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 921–930 of 6748 papers

Title	Date	Tasks	Status
A Formally Robust Time Series Distance Metric	Aug 18, 2020	ClassificationGeneral Classification	—Unverified
An Interpretable Machine Vision Approach to Human Activity Recognition using Photoplethysmograph Sensor Data	Dec 3, 2018	Activity RecognitionHuman Activity Recognition	—Unverified
A Convolutional Neural Network Approach to Supernova Time-Series Classification	Jul 19, 2022	ClassificationTime Series	—Unverified
bursty_dynamics: A Python Package for Exploring the Temporal Properties of Longitudinal Data	Nov 5, 2024	EpidemiologyTime Series Analysis	—Unverified
An interpretable LSTM neural network for autoregressive exogenous model	Apr 14, 2018	DecoderTime Series	—Unverified
GeoStat Representations of Time Series for Fast Classification	Jul 13, 2020	ClassificationDynamic Time Warping	—Unverified
A First Option Calibration of the GARCH Diffusion Model by a PDE Method	Jan 18, 2018	Time SeriesTime Series Analysis	—Unverified
An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series	Sep 2, 2022	Time SeriesTime Series Analysis	—Unverified
A first econometric analysis of the CRIX family	Sep 25, 2020	ClusteringDiagnostic	—Unverified
Bursty and persistent properties of large-scale brain networks revealed with a point-based method for dynamic functional connectivity	Jan 13, 2016	Functional ConnectivitySensitivity	—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