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 711–720 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection	Feb 15, 2022	Anomaly DetectionMissing Values	CodeCode Available	1	5
Multi-Time Attention Networks for Irregularly Sampled Time Series	Jan 25, 2021	Deep LearningTime Series	CodeCode Available	1	5
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests	Jul 14, 2021	Time SeriesTime Series Analysis	CodeCode Available	1	5
Multivariate Time-series Anomaly Detection via Graph Attention Network	Sep 4, 2020	Anomaly DetectionGraph Attention	CodeCode Available	1	5
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data	Jun 18, 2020	Causal DiscoveryTime Series	CodeCode Available	1	5
Deep Isolation Forest for Anomaly Detection	Jun 14, 2022	Anomaly DetectionTime Series	CodeCode Available	1	5
Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs	Feb 17, 2022	Multivariate Time Series ForecastingTime Series	CodeCode Available	1	5
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks	Jul 31, 2021	Graph Neural NetworkImputation	CodeCode Available	1	5
FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series Forecasting	Dec 2, 2022	Time SeriesTime Series Analysis	CodeCode Available	1	5
Federated Learning for 5G Base Station Traffic Forecasting	Nov 28, 2022	Federated LearningManagement	CodeCode Available	1	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