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 51–60 of 6748 papers

Title	Date	Tasks	Status	Hype
Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning	Feb 7, 2024	Contrastive LearningPrediction	CodeCode Available	2
MOMENT: A Family of Open Time-series Foundation Models	Feb 6, 2024	Time SeriesTime Series Analysis	CodeCode Available	2
Position: What Can Large Language Models Tell Us about Time Series Analysis	Feb 5, 2024	Decision MakingPosition	CodeCode Available	2
Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals	Feb 4, 2024	Ensemble LearningTime Series	CodeCode Available	2
Spatial-Temporal Large Language Model for Traffic Prediction	Jan 18, 2024	Language ModelingLanguage Modelling	CodeCode Available	2
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection	Jul 7, 2023	Anomaly DetectionImputation	CodeCode Available	2
FITS: Modeling Time Series with 10k Parameters	Jul 6, 2023	Anomaly DetectionTime Series	CodeCode Available	2
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects	Jun 16, 2023	Anomaly DetectionSelf-Supervised Learning	CodeCode Available	2
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series	May 30, 2023	Anomaly DetectionClassification	CodeCode Available	2
Model scale versus domain knowledge in statistical forecasting of chaotic systems	Mar 13, 2023	Time SeriesTime Series Analysis	CodeCode Available	2

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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