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 1151–1160 of 6748 papers

Title	Date	Tasks	Status
Near Optimal Heteroscedastic Regression with Symbiotic Learning	Jun 25, 2023	Econometricsregression	—Unverified
Deep learning-based deconvolution for interferometric radio transient reconstruction	Jun 24, 2023	AstronomyDeep Learning	CodeCode Available
Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United States	Jun 24, 2023	MisinformationSentiment Analysis	—Unverified
An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition	Jun 19, 2023	Feature EngineeringLoad Forecasting	—Unverified
Deep Learning for Energy Time-Series Analysis and Forecasting	Jun 15, 2023	Deep LearningDemand Forecasting	—Unverified
BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning	Jun 15, 2023	EEGElectroencephalogram (EEG)	—Unverified
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder	Jun 11, 2023	Anomaly DetectionContrastive Learning	CodeCode Available
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models	Jun 5, 2023	compressed sensingTime Series	—Unverified
Switching Autoregressive Low-rank Tensor Models	Jun 5, 2023	parameter estimationTime Series Analysis	CodeCode Available
An OPC UA-based industrial Big Data architecture	Jun 2, 2023	ERPTime Series	—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