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 2821–2830 of 6748 papers

Title	Date	Tasks	Status
Go with the FLOW: Visualizing spatiotemporal dynamics in optical widefield calcium imaging	Sep 29, 2020	Time SeriesTime Series Analysis	—Unverified
From Time Series to Euclidean Spaces: On Spatial Transformations for Temporal Clustering	Oct 2, 2020	ClusteringTime Series	—Unverified
Granger Causality: A Review and Recent Advances	May 5, 2021	Time SeriesTime Series Analysis	—Unverified
From time-series transcriptomics to gene regulatory networks: a review on inference methods	Oct 16, 2022	Time SeriesTime Series Analysis	—Unverified
Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models	Feb 16, 2023	Additive modelsLoad Forecasting	—Unverified
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting -- Full version	Mar 19, 2021	Correlated Time Series ForecastingGraph Attention	—Unverified
Conditional Generative Models for Counterfactual Explanations	Jan 25, 2021	counterfactualTime Series	—Unverified
Fully convolutional networks for structural health monitoring through multivariate time series classification	Feb 12, 2020	General ClassificationStructural Health Monitoring	—Unverified
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series	May 3, 2021	Deep LearningDenoising	—Unverified
Enhance the performance of navigation: A two-stage machine learning approach	Apr 2, 2020	BIG-bench Machine LearningEnsemble Learning	—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