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 1571–1580 of 6748 papers

Title	Date	Tasks	Status
AAMDRL: Augmented Asset Management with Deep Reinforcement Learning	Sep 30, 2020	Asset ManagementDeep Reinforcement Learning	—Unverified
A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting	Apr 20, 2020	Mathematical ProofsPrivacy Preserving	—Unverified
Critical Transitions in Intensive Care Units: A Sepsis Case Study	Oct 23, 2019	Time SeriesTime Series Analysis	—Unverified
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition	Sep 18, 2021	Anomaly DetectionTime Series	—Unverified
Learning low-dimensional state embeddings and metastable clusters from time series data	Jun 1, 2019	ClusteringTime Series	—Unverified
Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation	Oct 4, 2018	Drift DetectionTime Series	—Unverified
Crop Type Identification for Smallholding Farms: Analyzing Spatial, Temporal and Spectral Resolutions in Satellite Imagery	May 6, 2022	Time SeriesTime Series Analysis	—Unverified
Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning	Jun 24, 2020	Crop Yield PredictionExplainable Models	—Unverified
Cross-border Commodity Pricing Strategy Optimization via Mixed Neural Network for Time Series Analysis	Aug 22, 2024	Time SeriesTime Series Analysis	—Unverified
ArNet-ECG: Deep Learning for the Detection of Atrial Fibrillation from the Raw Electrocardiogram	Aug 22, 2022	Time SeriesTime Series Analysis	—Unverified

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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