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 1151–1160 of 6748 papers

Title	Date	Tasks	Status	Score
Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural Network	Oct 14, 2019	Graph Neural NetworkInductive Bias	CodeCode Available	5
Generative Adversarial Network for Future Hand Segmentation from Egocentric Video	Mar 21, 2022	Generative Adversarial NetworkHand Segmentation	CodeCode Available	5
Generating Sparse Counterfactual Explanations For Multivariate Time Series	Jun 2, 2022	counterfactualGenerative Adversarial Network	CodeCode Available	5
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions	Sep 30, 2019	Synthetic Data GenerationTime Series	CodeCode Available	5
Generating Reliable Process Event Streams and Time Series Data based on Neural Networks	Mar 9, 2021	Time SeriesTime Series Analysis	CodeCode Available	5
Generalised Label-free Artefact Cleaning for Real-time Medical Pulsatile Time Series	Apr 29, 2025	Decision MakingPhotoplethysmography (PPG)	CodeCode Available	5
Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting System	Jul 16, 2022	Data AugmentationDecoder	CodeCode Available	5
General anesthesia reduces complexity and temporal asymmetry of the informational structures derived from neural recordings in Drosophila	May 30, 2019	Time SeriesTime Series Analysis	CodeCode Available	5
GENDIS: GENetic DIscovery of Shapelets	Sep 13, 2019	Outlier DetectionTime Series	CodeCode Available	5
General Domain Adaptation Through Proportional Progressive Pseudo Labeling	Dec 23, 2020	Anomaly DetectionDomain Adaptation	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