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 591–600 of 6748 papers

Title	Date	Tasks	Status	Hype
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data	Apr 16, 2021	BenchmarkingCausal Discovery	CodeCode Available	1
An Empirical Study of Graph-Based Approaches for Semi-Supervised Time Series Classification	Apr 16, 2021	Binary ClassificationGeneral Classification	CodeCode Available	1
HIVE-COTE 2.0: a new meta ensemble for time series classification	Apr 15, 2021	General ClassificationTime Series	CodeCode Available	1
Adversarial Sticker: A Stealthy Attack Method in the Physical World	Apr 14, 2021	Face RecognitionImage Retrieval	CodeCode Available	1
Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations	Apr 13, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx	Apr 12, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Weak Form Generalized Hamiltonian Learning	Apr 11, 2021	FormTime Series	CodeCode Available	1
Deep Time Series Forecasting with Shape and Temporal Criteria	Apr 9, 2021	Change DetectionDiversity	CodeCode Available	1
DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales	Apr 9, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT	Apr 8, 2021	Anomaly DetectionTime Series	CodeCode Available	1

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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