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 1381–1390 of 6748 papers

Title	Date	Tasks	Status
A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow	Jan 6, 2023	Time SeriesTime Series Analysis	—Unverified
DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting	Jan 5, 2023	Probabilistic Time Series ForecastingTime Series	—Unverified
Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem	Jan 4, 2023	DecoderTime Series	—Unverified
Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy	Jan 4, 2023	counterfactualCounterfactual Explanation	—Unverified
PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time Series	Jan 4, 2023	Privacy PreservingTime Series	CodeCode Available
Graph state-space models	Jan 4, 2023	DecoderState Space Models	—Unverified
Recursive classification of satellite imaging time-series: An application to land cover mapping	Jan 4, 2023	ClassificationDecision Making	CodeCode Available
Covariate-guided Bayesian mixture model for multivariate time series	Jan 3, 2023	Mixture-of-ExpertsTime Series	CodeCode Available
Identifying Exoplanets with Deep Learning. V. Improved Light Curve Classification for TESS Full Frame Image Observations	Jan 3, 2023	Time Series Analysis	CodeCode Available
Common patterns between dengue cases, climate, and local environmental variables in Costa Rica: A Wavelet Approach	Jan 3, 2023	Time SeriesTime Series Analysis	—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