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 541–550 of 6748 papers

Title	Date	Tasks	Status	Hype
Causal Recurrent Variational Autoencoder for Medical Time Series Generation	Jan 16, 2023	Causal InferenceDecoder	CodeCode Available	1
Can Multimodal LLMs Perform Time Series Anomaly Detection?	Feb 25, 2025	Anomaly DetectionIrregular Time Series	CodeCode Available	1
Can LLMs Understand Time Series Anomalies?	Oct 7, 2024	Anomaly DetectionTime Series	CodeCode Available	1
CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level	May 3, 2022	Intrusion DetectionTime Series	CodeCode Available	1
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values	Feb 21, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection	Dec 17, 2020	Malware DetectionTime Series	CodeCode Available	1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks	May 24, 2020	Graph LearningGraph Neural Network	CodeCode Available	1
Changing Fashion Cultures	Mar 23, 2017	Cultural Vocal Bursts Intensity PredictionTime Series	CodeCode Available	1
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification	Jul 15, 2021	Conformal PredictionDeep Reinforcement Learning	CodeCode Available	1
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	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