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 411–420 of 6748 papers

Title	Date	Tasks	Status	Hype
Decoupling Local and Global Representations of Time Series	Feb 4, 2022	counterfactualTime Series	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
Methodology for forecasting and optimization in IEEE-CIS 3rd Technical Challenge	Feb 2, 2022	Load ForecastingMultivariate Time Series Forecasting	CodeCode Available	1
Similarity Learning based Few Shot Learning for ECG Time Series Classification	Jan 31, 2022	Dynamic Time WarpingFew-Shot Learning	CodeCode Available	1
Time-Series Anomaly Detection with Implicit Neural Representation	Jan 28, 2022	Anomaly DetectionTime Series	CodeCode Available	1
Neural Information Squeezer for Causal Emergence	Jan 25, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal	Jan 24, 2022	Cloud RemovalImage Reconstruction	CodeCode Available	1
Continual Transformers: Redundancy-Free Attention for Online Inference	Jan 17, 2022	Action DetectionAudio Classification	CodeCode Available	1
SwinUNet3D -- A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers	Jan 17, 2022	DecoderManagement	CodeCode Available	1
Time Series Generation with Masked Autoencoder	Jan 14, 2022	Data AugmentationDecoder	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