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 1951–1960 of 6748 papers

Title	Date	Tasks	Status	Score
Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex System	Jan 30, 2015	Time Series Analysis	CodeCode Available	5
Detection of Structural Change in Geographic Regions of Interest by Self Organized Mapping: Las Vegas City and Lake Mead across the Years	Mar 29, 2018	QuantizationTime Series	CodeCode Available	5
A Framework for Imbalanced Time-series Forecasting	Jul 22, 2021	Time SeriesTime Series Analysis	CodeCode Available	5
Bidirectional deep-readout echo state networks	Nov 17, 2017	ClassificationDimensionality Reduction	CodeCode Available	5
Deep Learning Detection of Inaccurate Smart Electricity Meters: A Case Study	Jul 26, 2019	Deep LearningTime Series Analysis	CodeCode Available	5
Diffeomorphic Temporal Alignment Nets	Dec 10, 2019	ECG ClassificationElectrocardiography (ECG)	CodeCode Available	5
Detecting structural perturbations from time series with deep learning	Jun 9, 2020	Bayesian InferenceDeep Learning	CodeCode Available	5
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability	Nov 16, 2017	Time SeriesTime Series Analysis	CodeCode Available	5
Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection	Apr 19, 2018	Anomaly DetectionFraud Detection	CodeCode Available	5
Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling	Jun 6, 2021	EconometricsTime Series	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