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 731–740 of 6748 papers

Title	Date	Tasks	Status	Hype
MegaCRN: Meta-Graph Convolutional Recurrent Network for Spatio-Temporal Modeling	Dec 12, 2022	DecoderGraph Learning	CodeCode Available	1
Memory-free Online Change-point Detection: A Novel Neural Network Approach	Jul 8, 2022	Change Point DetectionTime Series	CodeCode Available	1
Meta-learning framework with applications to zero-shot time-series forecasting	Feb 7, 2020	Meta-LearningTime Series	CodeCode Available	1
Methodology for forecasting and optimization in IEEE-CIS 3rd Technical Challenge	Feb 2, 2022	Load ForecastingMultivariate Time Series Forecasting	CodeCode Available	1
BolT: Fused Window Transformers for fMRI Time Series Analysis	May 23, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
Bilinear Input Normalization for Neural Networks in Financial Forecasting	Sep 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare	Jun 5, 2018	Gaussian ProcessesTime Series	CodeCode Available	1
Mixing Up Contrastive Learning: Self-Supervised Representation Learning for Time Series	Mar 17, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	Anomaly DetectionTime Series	CodeCode Available	1
Calibration of Google Trends Time Series	Jul 27, 2020	Time SeriesTime Series Analysis	CodeCode Available	1

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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