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 561–570 of 6748 papers

Title	Date	Tasks	Status	Hype
AGNet: Weighing Black Holes with Deep Learning	Aug 17, 2021	Deep LearningTime Series	CodeCode Available	1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks	May 24, 2020	Graph LearningGraph Neural Network	CodeCode Available	1
AGNet: Weighing Black Holes with Machine Learning	Nov 30, 2020	BIG-bench Machine LearningTime Series	CodeCode Available	1
Continual Transformers: Redundancy-Free Attention for Online Inference	Jan 17, 2022	Action DetectionAudio Classification	CodeCode Available	1
Continuous-Time Deep Glioma Growth Models	Jun 23, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations	Jun 16, 2022	Causal Inferencecounterfactual	CodeCode Available	1
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting	Sep 15, 2021	Decision MakingProbabilistic Time Series Forecasting	CodeCode Available	1
Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets	Sep 28, 2021	ClassificationTime Series	CodeCode Available	1
Copula Conformal Prediction for Multi-step Time Series Forecasting	Dec 6, 2022	Conformal PredictionPrediction	CodeCode Available	1
Benchmark time series data sets for PyTorch -- the torchtime package	Jul 25, 2022	Time SeriesTime Series Analysis	CodeCode Available	1

Show:10 25 50

← PrevPage 57 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