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 1261–1270 of 6748 papers

Title	Date	Tasks	Status	Score
Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach	Oct 9, 2017	BenchmarkingClustering	CodeCode Available	5
A mathematical perspective on edge-centric brain functional connectivity	Jun 20, 2021	Functional ConnectivityTime Series	CodeCode Available	5
Accurate Characterization of Non-Uniformly Sampled Time Series using Stochastic Differential Equations	Jul 2, 2020	Bayesian OptimizationCompressive Sensing	CodeCode Available	5
A Recurrent Neural Network Survival Model: Predicting Web User Return Time	Jul 11, 2018	Survival AnalysisTime Series	CodeCode Available	5
Forecasting Algorithms for Causal Inference with Panel Data	Aug 6, 2022	Causal Inferencecounterfactual	CodeCode Available	5
A machine learning framework for computationally expensive transient models	Jul 12, 2019	BIG-bench Machine LearningTime Series	CodeCode Available	5
fETSmcs: Feature-based ETS model component selection	Jun 26, 2022	modelModel Selection	CodeCode Available	5
Feature space approximation for kernel-based supervised learning	Nov 25, 2020	regressionTime Series	CodeCode Available	5
Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methods	Sep 30, 2021	feature selectionTime Series	CodeCode Available	5
Feature Selection for Multivariate Time Series via Network Pruning	Feb 11, 2021	feature selectionNetwork Pruning	CodeCode Available	5

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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