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 731–740 of 6748 papers

Title	Date	Tasks	Status	Hype
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data	Jul 20, 2020	Few-Shot LearningMulti-Task Learning	CodeCode Available	1
COVID-19 Data Analysis and Forecasting: Algeria and the World	Jul 19, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Modeling Financial Time Series using LSTM with Trainable Initial Hidden States	Jul 14, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Long Short-Term Memory Spiking Networks and Their Applications	Jul 9, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Fast Variational Learning in State-Space Gaussian Process Models	Jul 9, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Learning Differential Equations that are Easy to Solve	Jul 9, 2020	Density EstimationTime Series	CodeCode Available	1
Few-Shot One-Class Classification via Meta-Learning	Jul 8, 2020	Anomaly DetectionClassification	CodeCode Available	1
Superiority of Simplicity: A Lightweight Model for Network Device Workload Prediction	Jul 7, 2020	CPUTime Series Analysis	CodeCode Available	1
MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity	Jul 7, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Leveraging Class Hierarchies with Metric-Guided Prototype Learning	Jul 6, 2020	General ClassificationSemantic Segmentation	CodeCode Available	1

Show:10 25 50

← PrevPage 74 of 675Next →

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