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 521–530 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
Dynamical Wasserstein Barycenters for Time-series Modeling	Oct 13, 2021	State EstimationTime Series	CodeCode Available	1	5
Dynamic Data Augmentation with Gating Networks for Time Series Recognition	Nov 5, 2021	Data AugmentationTime Series	CodeCode Available	1	5
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series	Mar 3, 2021	ClusteringTime Series	CodeCode Available	1	5
Dynamic Sparse Network for Time Series Classification: Learning What to "see''	Dec 19, 2022	Time SeriesTime Series Analysis	CodeCode Available	1	5
InceptionTime: Finding AlexNet for Time Series Classification	Sep 11, 2019	Deep LearningGeneral Classification	CodeCode Available	1	5
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels	Jul 12, 2022	Action DetectionActivity Detection	CodeCode Available	1	5
DTAAD: Dual Tcn-Attention Networks for Anomaly Detection in Multivariate Time Series Data	Feb 17, 2023	Anomaly DetectionDiagnostic	CodeCode Available	1	5
A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning	Apr 2, 2022	Crop ClassificationSemantic Segmentation	CodeCode Available	1	5
Do We Really Need Deep Learning Models for Time Series Forecasting?	Jan 6, 2021	Deep Learningregression	CodeCode Available	1	5
Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting	Aug 5, 2022	Time SeriesTime Series Analysis	CodeCode Available	1	5

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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