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 401–410 of 6748 papers

Title	Date	Tasks	Status	Hype
FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series Forecasting	Dec 2, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
FedMood: Federated Learning on Mobile Health Data for Mood Detection	Feb 6, 2021	BIG-bench Machine LearningDepression Detection	CodeCode Available	1
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection	Jun 15, 2021	Anomaly DetectionFederated Learning	CodeCode Available	1
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments	Jun 26, 2021	High-Level SynthesisTime Series	CodeCode Available	1
Few-Shot Forecasting of Time-Series with Heterogeneous Channels	Apr 7, 2022	ClassificationTime Series	CodeCode Available	1
Few-Shot One-Class Classification via Meta-Learning	Jul 8, 2020	Anomaly DetectionClassification	CodeCode Available	1
Changing Fashion Cultures	Mar 23, 2017	Cultural Vocal Bursts Intensity PredictionTime Series	CodeCode Available	1
Finding Scientific Topics in Continuously Growing Text Corpora	Oct 1, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
FingerFlex: Inferring Finger Trajectories from ECoG signals	Oct 23, 2022	Brain Computer InterfaceBrain Decoding	CodeCode Available	1
An efficient aggregation method for the symbolic representation of temporal data	Jan 14, 2022	Dimensionality ReductionInformation Retrieval	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