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 1621–1630 of 6748 papers

Title	Date	Tasks	Status	Score
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification	Nov 3, 2022	Contrastive Learningparameter estimation	CodeCode Available	5
E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction	Feb 22, 2019	DecoderLink Prediction	CodeCode Available	5
Emergence of Functionally Differentiated Structures via Mutual Information Optimization in Recurrent Neural Networks	Jul 17, 2025	Time Series Analysis	CodeCode Available	5
Elastic Product Quantization for Time Series	Jan 4, 2022	QuantizationTime Series	CodeCode Available	5
Data augmentation using synthetic data for time series classification with deep residual networks	Aug 7, 2018	Data AugmentationDynamic Time Warping	CodeCode Available	5
Data Consistency Approach to Model Validation	Aug 17, 2018	modelTime Series	CodeCode Available	5
Elastic bands across the path: A new framework and methods to lower bound DTW	Aug 29, 2018	ClusteringDynamic Time Warping	CodeCode Available	5
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation	Jan 29, 2019	Time SeriesTime Series Analysis	CodeCode Available	5
Elastic Similarity and Distance Measures for Multivariate Time Series	Feb 20, 2021	ClassificationDynamic Time Warping	CodeCode Available	5
Efficient Matrix Profile Computation Using Different Distance Functions	Jan 17, 2019	Time SeriesTime Series Analysis	CodeCode Available	5

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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