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 891–900 of 6748 papers

Title	Date	Tasks	Status	Hype
Multitask learning and benchmarking with clinical time series data	Mar 22, 2017	BenchmarkingBIG-bench Machine Learning	CodeCode Available	1
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks	Mar 21, 2017	Multivariate Time Series ForecastingTime Series	CodeCode Available	1
Soft-DTW: a Differentiable Loss Function for Time-Series	Mar 5, 2017	Dynamic Time WarpingTime Series	CodeCode Available	1
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing	Nov 7, 2016	Activity RecognitionGeneral Classification	CodeCode Available	1
Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models	Oct 7, 2016	DiversityImage Captioning	CodeCode Available	1
On the adoption of abductive reasoning for time series interpretation	Sep 19, 2016	General ClassificationTime Series	CodeCode Available	1
Recurrent Neural Networks for Multivariate Time Series with Missing Values	Jun 6, 2016	ImputationMissing Values	CodeCode Available	1
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA	May 20, 2016	Contrastive LearningTime Series	CodeCode Available	1
Convolutional Radio Modulation Recognition Networks	Feb 12, 2016	General ClassificationTime Series	CodeCode Available	1
Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark	Oct 12, 2015	Anomaly DetectionTime Series	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