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 711–720 of 6748 papers

Title	Date	Tasks	Status	Hype
Bilinear Input Normalization for Neural Networks in Financial Forecasting	Sep 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Light curve completion and forecasting using fast and scalable Gaussian processes (MuyGPs)	Aug 31, 2022	Gaussian ProcessesPose Estimation	CodeCode Available	1
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	Anomaly DetectionTime Series	CodeCode Available	1
Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series	Jul 1, 2020	Earth ObservationTime Series	CodeCode Available	1
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data	Jun 18, 2020	Causal DiscoveryTime Series	CodeCode Available	1
Benchmarking Deep Learning Interpretability in Time Series Predictions	Oct 26, 2020	BenchmarkingDeep Learning	CodeCode Available	1
Local Evaluation of Time Series Anomaly Detection Algorithms	Jun 27, 2022	Anomaly DetectionTime Series	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
Long Short-Term Memory Spiking Networks and Their Applications	Jul 9, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Benchmark time series data sets for PyTorch -- the torchtime package	Jul 25, 2022	Time SeriesTime Series Analysis	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