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 361–370 of 6748 papers

Title	Date	Tasks	Status	Hype
Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant Representation	Aug 21, 2020	Change Point DetectionTime Series	CodeCode Available	1
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting	Jul 6, 2017	DecoderMultivariate Time Series Forecasting	CodeCode Available	1
Chaos as an interpretable benchmark for forecasting and data-driven modelling	Oct 11, 2021	BenchmarkingSymbolic Regression	CodeCode Available	1
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations	Mar 3, 2022	Decision MakingDisentanglement	CodeCode Available	1
Discovering Nonlinear Relations with Minimum Predictive Information Regularization	Jan 7, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Discrete Graph Structure Learning for Forecasting Multiple Time Series	Jan 18, 2021	Graph structure learningTime Series	CodeCode Available	1
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis	Oct 18, 2023	Anomaly DetectionImputation	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
Causal Recurrent Variational Autoencoder for Medical Time Series Generation	Jan 16, 2023	Causal InferenceDecoder	CodeCode Available	1
Causal Forecasting:Generalization Bounds for Autoregressive Models	Nov 18, 2021	Learning TheoryTime Series	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