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 1591–1600 of 6748 papers

Title	Date	Tasks	Status
Preparing fMRI Data for Statistical Analysis	Oct 24, 2022	DenoisingTime Series	—Unverified
Novelty Detection in Time Series via Weak Innovations Representation: A Deep Learning Approach	Oct 24, 2022	Novelty DetectionTime Series	—Unverified
Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble	Oct 24, 2022	Demand ForecastingLoad Forecasting	—Unverified
Applications of Machine Learning in Pharmacogenomics: Clustering Plasma Concentration-Time Curves	Oct 24, 2022	ClusteringData Visualization	—Unverified
Exploring Self-Attention for Crop-type Classification Explainability	Oct 24, 2022	ClassificationTime Series Analysis	—Unverified
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior	Oct 22, 2022	Inductive BiasTime Series	—Unverified
Time Series Synthesis via Multi-scale Patch-based Generation of Wavelet Scalogram	Oct 21, 2022	DiversityTime Series	—Unverified
Theoretical analysis of deep neural networks for temporally dependent observations	Oct 20, 2022	Time SeriesTime Series Analysis	—Unverified
Multimodal Neural Network For Demand Forecasting	Oct 20, 2022	ArticlesDemand Forecasting	—Unverified
Irregularly-Sampled Time Series Modeling with Spline Networks	Oct 19, 2022	Missing ValuesTime 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