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 341–350 of 6748 papers

Title	Date	Tasks	Status	Hype	Score
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting	Jul 6, 2017	DecoderMultivariate Time Series Forecasting	CodeCode Available	1	5
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time Warping	Nov 26, 2021	Dynamic Time WarpingTime Series	CodeCode Available	1	5
AA-Forecast: Anomaly-Aware Forecast for Extreme Events	Aug 21, 2022	Anomaly ForecastingMultivariate Time Series Forecasting	CodeCode Available	1	5
Automatic Change-Point Detection in Time Series via Deep Learning	Nov 7, 2022	Change Point DetectionDeep Learning	CodeCode Available	1	5
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly Detection	Aug 19, 2022	Anomaly DetectionRepresentation Learning	CodeCode Available	1	5
Discovering Nonlinear Relations with Minimum Predictive Information Regularization	Jan 7, 2020	Time SeriesTime Series Analysis	CodeCode Available	1	5
Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines	Jun 26, 2021	BIG-bench Machine LearningManagement	CodeCode Available	1	5
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA	Jun 17, 2021	Dimensionality ReductionDisentanglement	CodeCode Available	1	5
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models	Oct 7, 2016	DiversityImage Captioning	CodeCode Available	1	5
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments	Jun 26, 2021	High-Level SynthesisTime Series	CodeCode Available	1	5

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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