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 4251–4260 of 6748 papers

Title	Date	Tasks	Status
Weather Prediction Using CNN-LSTM for Time Series Analysis: A Case Study on Delhi Temperature Data	Sep 14, 2024	energy managementTime Series	—Unverified
Weighted Isolation and Random Cut Forest Algorithms for Anomaly Detection	Feb 1, 2022	Anomaly DetectionTime Series Analysis	—Unverified
WEITS: A Wavelet-enhanced residual framework for interpretable time series forecasting	May 17, 2024	Time SeriesTime Series Analysis	—Unverified
What is the best RNN-cell structure for forecasting each time series behavior?	Mar 15, 2022	Time SeriesTime Series Analysis	—Unverified
What Makes An Asset Useful?	Jun 21, 2018	Time SeriesTime Series Analysis	—Unverified
What went wrong and when? Instance-wise Feature Importance for Time-series Models	Mar 5, 2020	counterfactualFeature Importance	—Unverified
What went wrong and when?\\ Instance-wise feature importance for time-series black-box models	Dec 1, 2020	counterfactualFeature Importance	—Unverified
When Complexity Is Good: Do We Need Recurrent Deep Learning For Time Series Outlier Detection?	Sep 29, 2021	Home Activity MonitoringOutlier Detection	—Unverified
When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming	Sep 27, 2014	Time SeriesTime Series Analysis	—Unverified
When is Early Classification of Time Series Meaningful?	Feb 23, 2021	ClassificationEarly Classification	—Unverified

Show:10 25 50

← PrevPage 426 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