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 581–590 of 6748 papers

Title	Date	Tasks	Status	Hype
Monash Time Series Forecasting Archive	May 14, 2021	Missing ValuesTime Series	CodeCode Available	1
Quantified Sleep: Machine learning techniques for observational n-of-1 studies	May 14, 2021	BIG-bench Machine LearningDescriptive	CodeCode Available	1
Paying Attention to Astronomical Transients: Introducing the Time-series Transformer for Photometric Classification	May 13, 2021	Classificationfeature selection	CodeCode Available	1
Real-Time Anomaly Detection and Feature Analysis Based on Time Series for Surveillance Video	May 11, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
SIRNN: A Math Library for Secure RNN Inference	May 10, 2021	Time Series Analysis	CodeCode Available	1
Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting	May 10, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Neural graphical modelling in continuous-time: consistency guarantees and algorithms	May 6, 2021	Causal DiscoveryGraph Learning	CodeCode Available	1
Using Twitter Attribute Information to Predict Stock Prices	May 4, 2021	AttributeBIG-bench Machine Learning	CodeCode Available	1
Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling	Apr 30, 2021	Recommendation SystemsThompson Sampling	CodeCode Available	1
Learning future terrorist targets through temporal meta-graphs	Apr 21, 2021	HumanitarianTemporal Sequences	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