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 831–840 of 6748 papers

Title	Date	Tasks	Status	Hype
Backdoor Attacks on Time Series: A Generative Approach	Nov 15, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models	Jun 18, 2021	Probabilistic Time Series ForecastingTime Series	CodeCode Available	1
Score Matched Neural Exponential Families for Likelihood-Free Inference	Dec 20, 2020	Bayesian InferenceTime Series	CodeCode Available	1
A Transformer-based Framework for Multivariate Time Series Representation Learning	Oct 6, 2020	Computational EfficiencyGeneral Classification	CodeCode Available	1
Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection	Jul 25, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available	1
Self-supervised Autoregressive Domain Adaptation for Time Series Data	Nov 29, 2021	Domain AdaptationSelf-Supervised Learning	CodeCode Available	1
Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting	Sep 4, 2021	Irregular Time SeriesRepresentation Learning	CodeCode Available	1
BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief Propagation	Jun 13, 2023	Heart rate estimationPhotoplethysmography (PPG) heart rate estimation	CodeCode Available	1
Axial-LOB: High-Frequency Trading with Axial Attention	Dec 4, 2022	Time SeriesTime Series Analysis	CodeCode Available	1
Abstracted Shapes as Tokens -- A Generalizable and Interpretable Model for Time-series Classification	Nov 1, 2024	QuantizationRepresentation Learning	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