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	Score
Deep Semi-Supervised Learning for Time Series Classification	Feb 6, 2021	ClassificationData Augmentation	CodeCode Available	1	5
Neural Ordinary Differential Equations for Intervention Modeling	Oct 16, 2020	Time SeriesTime Series Analysis	CodeCode Available	1	5
Few-Shot Forecasting of Time-Series with Heterogeneous Channels	Apr 7, 2022	ClassificationTime Series	CodeCode Available	1	5
A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons	Feb 28, 2020	Time Series Analysis	CodeCode Available	1	5
Few-Shot One-Class Classification via Meta-Learning	Jul 8, 2020	Anomaly DetectionClassification	CodeCode Available	1	5
FedTADBench: Federated Time-Series Anomaly Detection Benchmark	Dec 19, 2022	Anomaly DetectionFederated Learning	CodeCode Available	1	5
Deep Switching State Space Model (DS^3M) for Nonlinear Time Series Forecasting with Regime Switching	Jun 4, 2021	Time SeriesTime Series Analysis	CodeCode Available	1	5
Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting	Sep 10, 2020	Time SeriesTime Series Analysis	CodeCode Available	1	5
Deeptime: a Python library for machine learning dynamical models from time series data	Oct 28, 2021	Time SeriesTime Series Analysis	CodeCode Available	1	5
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting	May 18, 2022	Deep LearningDimensionality Reduction	CodeCode Available	1	5

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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