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 781–790 of 6748 papers

Title	Date	Tasks	Status	Hype
NRTSI: Non-Recurrent Time Series Imputation	Feb 5, 2021	ImputationTime Series	CodeCode Available	1
Can LLMs Understand Time Series Anomalies?	Oct 7, 2024	Anomaly DetectionTime Series	CodeCode Available	1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning	Sep 30, 2021	Activity RecognitionContrastive Learning	CodeCode Available	1
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	Sep 9, 2019	Object LocalizationPrediction	CodeCode Available	1
One Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data	Feb 13, 2023	AllTime Series	CodeCode Available	1
Online Change Point Detection in Molecular Dynamics With Optical Random Features	Jun 15, 2020	Change Point DetectionTime Series	CodeCode Available	1
Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection	Jul 25, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available	1
On the adoption of abductive reasoning for time series interpretation	Sep 19, 2016	General ClassificationTime Series	CodeCode Available	1
On time series representations for multi-label NILM	May 2, 2020	Dimensionality ReductionNon-Intrusive Load Monitoring	CodeCode Available	1
Can Multimodal LLMs Perform Time Series Anomaly Detection?	Feb 25, 2025	Anomaly DetectionIrregular Time 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