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 851–860 of 6748 papers

Title	Date	Tasks	Status	Hype
Attention to Warp: Deep Metric Learning for Multivariate Time Series	Mar 28, 2021	Dynamic Time WarpingMetric Learning	CodeCode Available	1
Skeleton-Based Action Segmentation with Multi-Stage Spatial-Temporal Graph Convolutional Neural Networks	Feb 3, 2022	Action SegmentationSkeleton Based Action Segmentation	CodeCode Available	1
Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting	Sep 4, 2021	Irregular Time SeriesRepresentation Learning	CodeCode Available	1
An efficient aggregation method for the symbolic representation of temporal data	Jan 14, 2022	Dimensionality ReductionInformation Retrieval	CodeCode Available	1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning	Sep 30, 2021	Activity RecognitionContrastive Learning	CodeCode Available	1
Soft-DTW: a Differentiable Loss Function for Time-Series	Mar 5, 2017	Dynamic Time WarpingTime Series	CodeCode Available	1
Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks	Nov 11, 2020	Density EstimationTime Series	CodeCode Available	1
SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series	May 31, 2022	Contrastive LearningDimensionality Reduction	CodeCode Available	1
S&P 500 Stock Price Prediction Using Technical, Fundamental and Text Data	Aug 24, 2021	BIG-bench Machine LearningPrediction	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