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 811–820 of 6748 papers

Title	Date	Tasks	Status	Hype
An Evaluation of Change Point Detection Algorithms	Mar 13, 2020	Change Point DetectionTime Series	CodeCode Available	1
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution	Mar 9, 2020	AttributeKnowledge Graphs	CodeCode Available	1
FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks	Mar 9, 2020	PositionSegmentation	CodeCode Available	1
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models	Mar 8, 2020	Decision MakingTime Series	CodeCode Available	1
On the performance of deep learning models for time series classification in streaming	Mar 5, 2020	General ClassificationTime Series	CodeCode Available	1
Forecasting Sequential Data using Consistent Koopman Autoencoders	Mar 4, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Dimensionality reduction to maximize prediction generalization capability	Mar 1, 2020	Dimensionality ReductionPrediction	CodeCode Available	1
A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons	Feb 28, 2020	Time Series Analysis	CodeCode Available	1
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows	Feb 24, 2020	Density EstimationIrregular Time Series	CodeCode Available	1
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification	Feb 24, 2020	General ClassificationTime 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