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 3211–3220 of 6748 papers

Title	Date	Tasks	Status
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems	Apr 29, 2020	Multi-Task Learningregression	—Unverified
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis	Dec 11, 2023	Data AugmentationDeep Learning	—Unverified
Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial Networks	May 13, 2022	Data AugmentationTime Series	—Unverified
Causal Consistency of Structural Equation Models	Jul 4, 2017	Time SeriesTime Series Analysis	—Unverified
Improving Clinical Predictions through Unsupervised Time Series Representation Learning	Dec 2, 2018	Decision MakingRepresentation Learning	—Unverified
Improving Convolutional Neural Networks for Fault Diagnosis by Assimilating Global Features	Oct 3, 2022	Fault DiagnosisTime Series Analysis	—Unverified
D2KE: From Distance to Kernel and Embedding	Feb 14, 2018	Time Series Analysis	—Unverified
Causal Compression	Nov 1, 2016	Time SeriesTime Series Analysis	—Unverified
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition	Dec 30, 2018	Time SeriesTime Series Analysis	—Unverified
Embedding Symbolic Temporal Knowledge into Deep Sequential Models	Jan 28, 2021	Action RecognitionActivity Recognition	—Unverified

Show:10 25 50

← PrevPage 322 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