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 1211–1220 of 6748 papers

Title	Date	Tasks	Status	Score
Forecasting with Multiple Seasonality	Aug 27, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
Forecasting the Leading Indicator of a Recession: The 10-Year minus 3-Month Treasury Yield Spread	Sep 7, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the Covid-19 case	Jan 19, 2022	ManagementTime Series	CodeCode Available	5
Forecasting new diseases in low-data settings using transfer learning	Apr 7, 2022	Time Series AnalysisTransfer Learning	CodeCode Available	5
Forecasting COVID-19 Counts At A Single Hospital: A Hierarchical Bayesian Approach	Apr 14, 2021	Time SeriesTime Series Analysis	CodeCode Available	5
A Multi-Horizon Quantile Recurrent Forecaster	Nov 29, 2017	quantile regressionregression	CodeCode Available	5
Forecasting Precipitable Water Vapor Using LSTMs	Jun 26, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies	Jun 27, 2017	Time SeriesTime Series Analysis	CodeCode Available	5
Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach	Oct 9, 2017	BenchmarkingClustering	CodeCode Available	5
Forecasting Algorithms for Causal Inference with Panel Data	Aug 6, 2022	Causal Inferencecounterfactual	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