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 1241–1250 of 6748 papers

Title	Date	Tasks	Status
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles	Feb 22, 2023	Bayesian OptimizationDiversity	—Unverified
Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference	Feb 22, 2023	Causal Inferencecounterfactual	—Unverified
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting	Feb 22, 2023	Time SeriesTime Series Analysis	—Unverified
The DeepCAR Method: Forecasting Time-Series Data That Have Change Points	Feb 22, 2023	Time SeriesTime Series Analysis	CodeCode Available
Time-varying Signals Recovery via Graph Neural Networks	Feb 22, 2023	DecoderGraph Learning	—Unverified
Information Theory Inspired Pattern Analysis for Time-series Data	Feb 22, 2023	Time SeriesTime Series Analysis	—Unverified
Measuring city-scale green infrastructure drawdown dynamics using internet-connected sensors in Detroit	Feb 21, 2023	Time SeriesTime Series Analysis	—Unverified
TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts	Feb 21, 2023	Image GenerationTime Series	—Unverified
Task-Oriented Prediction and Communication Co-Design for Haptic Communications	Feb 21, 2023	PredictionTime Series	—Unverified
FedST: Secure Federated Shapelet Transformation for Time Series Classification	Feb 21, 2023	ClassificationFederated Learning	—Unverified

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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