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 3451–3460 of 6748 papers

Title	Date	Tasks	Status
Gaussian Processes with Skewed Laplace Spectral Mixture Kernels for Long-term Forecasting	Nov 8, 2020	Gaussian ProcessesTime Series Analysis	—Unverified
Skill Analysis with Time Series Image Data	Jan 21, 2014	Time SeriesTime Series Analysis	—Unverified
Skill-Based Differences in Spatio-Temporal Team Behavior in Defence of The Ancients 2	Mar 24, 2016	ClusteringDota 2	—Unverified
sktime: A Unified Interface for Machine Learning with Time Series	Sep 17, 2019	BIG-bench Machine LearningTime Series	—Unverified
Sleep Analytics and Online Selective Anomaly Detection	Mar 2, 2014	Anomaly DetectionEEG	—Unverified
SleepNet: Automated Sleep Analysis via Dense Convolutional Neural Network Using Physiological Time Series	Mar 11, 2019	Multi-Task LearningTime Series	—Unverified
SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmography	Feb 11, 2022	ManagementPhotoplethysmography (PPG)	—Unverified
SleepPriorCL: Contrastive Representation Learning with Prior Knowledge-based Positive Mining and Adaptive Temperature for Sleep Staging	Oct 15, 2021	Representation LearningSelf-Supervised Learning	—Unverified
Sliding Spectrum Decomposition for Diversified Recommendation	Jul 12, 2021	DiversityRecommendation Systems	—Unverified
Sliding Window Sum Algorithms for Deep Neural Networks	May 25, 2023	CPUGPU	—Unverified

Show:10 25 50

← PrevPage 346 of 675Next →

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