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 511–520 of 6748 papers

Title	Date	Tasks	Status	Hype
S&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data	Aug 24, 2021	BIG-bench Machine LearningPrediction	CodeCode Available	1
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction	Aug 20, 2021	Deep LearningTime Series	CodeCode Available	1
AGNet: Weighing Black Holes with Deep Learning	Aug 17, 2021	Deep LearningTime Series	CodeCode Available	1
Data-driven discovery of intrinsic dynamics	Aug 12, 2021	Time Series Analysis	CodeCode Available	1
Predicting in-hospital mortality by combining clinical notes with time-series data	Aug 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Multi-module Recurrent Convolutional Neural Network with Transformer Encoder for ECG Arrhythmia Classification	Aug 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks	Jul 31, 2021	Graph Neural NetworkImputation	CodeCode Available	1
Temporal Dependencies in Feature Importance for Time Series Predictions	Jul 29, 2021	Feature ImportanceTime Series	CodeCode Available	1
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series	Jul 29, 2021	ImputationMortality Prediction	CodeCode Available	1
Generative adversarial networks in time series: A survey and taxonomy	Jul 23, 2021	SurveyTime Series	CodeCode Available	1

Show:10 25 50

← PrevPage 52 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