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 551–560 of 6748 papers

Title	Date	Tasks	Status	Hype
ClaSP -- Parameter-free Time Series Segmentation	Jul 28, 2022	Change Point DetectionSegmentation	CodeCode Available	1
Contrastive Neural Processes for Self-Supervised Learning	Oct 24, 2021	Contrastive LearningData Augmentation	CodeCode Available	1
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation	May 14, 2020	General ClassificationSpecificity	CodeCode Available	1
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks	Jan 6, 2022	Audio ClassificationClassification	CodeCode Available	1
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	Sep 9, 2019	Object LocalizationPrediction	CodeCode Available	1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning	Jun 23, 2020	Knowledge GraphsMulti-Task Learning	CodeCode Available	1
Closed-Form Diffeomorphic Transformations for Time Series Alignment	Jun 16, 2022	CPUForm	CodeCode Available	1
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data	Jul 24, 2022	Anomaly DetectionAutonomous Driving	CodeCode Available	1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent Autoencoders	Dec 5, 2021	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

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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