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 211–220 of 6748 papers

Title	Date	Tasks	Status	Hype
Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG	Jan 3, 2023	Anomaly DetectionEEG	CodeCode Available	1
Follow the Timeline! Generating Abstractive and Extractive Timeline Summary in Chronological Order	Jan 2, 2023	DecoderDocument Summarization	CodeCode Available	1
Multi-step-ahead Stock Price Prediction Using Recurrent Fuzzy Neural Network and Variational Mode Decomposition	Dec 24, 2022	PredictionStock Price Prediction	CodeCode Available	1
Deep Latent State Space Models for Time-Series Generation	Dec 24, 2022	State Space ModelsTime Series	CodeCode Available	1
FedTADBench: Federated Time-Series Anomaly Detection Benchmark	Dec 19, 2022	Anomaly DetectionFederated Learning	CodeCode Available	1
Dynamic Sparse Network for Time Series Classification: Learning What to "see''	Dec 19, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
Convolution-enhanced Evolving Attention Networks	Dec 16, 2022	image-classificationImage Classification	CodeCode Available	1
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting	Dec 15, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics	Dec 15, 2022	Data IntegrationTime Series	CodeCode Available	1
Temporal Saliency Detection Towards Explainable Transformer-based Timeseries Forecasting	Dec 15, 2022	DecoderSaliency Detection	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