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 3351–3360 of 6748 papers

Title	Date	Tasks	Status
Jumpy Recurrent Neural Networks	Jan 1, 2021	Time SeriesTime Series Analysis	—Unverified
Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series	Sep 15, 2021	Time SeriesTime Series Analysis	—Unverified
Interpretable Categorization of Heterogeneous Time Series Data	Aug 30, 2017	ClusteringCollision Avoidance	—Unverified
Interpretable Classification of Time-Series Data using Efficient Enumerative Techniques	Jul 24, 2019	Autonomous VehiclesClassification	—Unverified
A Novel CNN-LSTM-based Approach to Predict Urban Expansion	Mar 2, 2021	Image SegmentationSemantic Segmentation	—Unverified
Interpretable Deep Learning for Forecasting Online Advertising Costs: Insights from the Competitive Bidding Landscape	Feb 11, 2023	ClusteringFeature Importance	—Unverified
Interpretable Feature Construction for Time Series Extrinsic Regression	Mar 15, 2021	Benchmarkingregression	—Unverified
Interpretable Feature Engineering for Time Series Predictors using Attention Networks	May 23, 2022	Feature EngineeringTime Series	—Unverified
Interpretable Latent Variables in Deep State Space Models	Mar 3, 2022	DecoderState Space Models	—Unverified
A Graph-constrained Changepoint Detection Approach for ECG Segmentation	Apr 24, 2020	QRS Complex DetectionTime Series	—Unverified

Show:10 25 50

← PrevPage 336 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