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 1321–1330 of 6748 papers

Title	Date	Tasks	Status	Score
Applying Machine Learning to Crowd-sourced Data from Earthquake Detective	Nov 5, 2020	BIG-bench Machine LearningTime Series	CodeCode Available	5
Forecasting with Multiple Seasonality	Aug 27, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time series data	Sep 13, 2022	Time SeriesTime Series Analysis	CodeCode Available	5
Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound	Nov 20, 2008	Dynamic Time WarpingRetrieval	CodeCode Available	5
Sequence Prediction using Spectral RNNs	Dec 13, 2018	PredictionTime Series	CodeCode Available	5
Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm	Jul 7, 2019	GPUTime Series	CodeCode Available	5
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs	Apr 12, 2018	regressionTime Series	CodeCode Available	5
Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling	Jun 6, 2021	EconometricsTime Series	CodeCode Available	5
Fast and Accurate Time Series Classification with WEASEL	Jan 26, 2017	ClassificationGeneral Classification	CodeCode Available	5
Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series Classifiers	Oct 2, 2022	Pose EstimationPose Tracking	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