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 4141–4150 of 6748 papers

Title	Date	Tasks	Status
Unsupervised Prediction of Negative Health Events Ahead of Time	Jan 31, 2019	Anomaly DetectionClustering	—Unverified
Unsupervised Representation for EHR Signals and Codes as Patient Status Vector	Oct 4, 2019	Representation LearningTime Series	—Unverified
Unsupervised Representation Learning and Anomaly Detection in ECG Sequences	Aug 1, 2019	Anomaly DetectionClustering	—Unverified
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles -- Extended Version	Nov 22, 2021	DiversityOutlier Detection	—Unverified
Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion	Feb 8, 2022	Anomaly DetectionContrastive Learning	—Unverified
Unsupervised Visual Time-Series Representation Learning and Clustering	Nov 19, 2021	Autonomous DrivingClustering	—Unverified
Untargeted, Targeted and Universal Adversarial Attacks and Defenses on Time Series	Jan 13, 2021	Adversarial AttackAdversarial Defense	—Unverified
Exploring Representations and Interventions in Time Series Foundation Models	Sep 19, 2024	Time SeriesTime Series Analysis	—Unverified
Unveiling Early Warning Signals of Systemic Risks in Banks: A Recurrence Network-Based Approach	Oct 16, 2023	Time SeriesTime Series Analysis	—Unverified
Unveiling the role of plasticity rules in reservoir computing	Jan 14, 2021	Time Series AnalysisTime Series Prediction	—Unverified

Show:10 25 50

← PrevPage 415 of 675Next →

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