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 551–560 of 6748 papers

Title	Date	Tasks	Status	Hype
On Contrastive Representations of Stochastic Processes	Jun 18, 2021	Meta-LearningTime Series	CodeCode Available	1
pyWATTS: Python Workflow Automation Tool for Time Series	Jun 18, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks	Jun 18, 2021	Graph AttentionTime Series	CodeCode Available	1
Voice2Series: Reprogramming Acoustic Models for Time Series Classification	Jun 17, 2021	ClassificationData Augmentation	CodeCode Available	1
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA	Jun 17, 2021	Dimensionality ReductionDisentanglement	CodeCode Available	1
SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction	Jun 17, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection	Jun 15, 2021	Anomaly DetectionFederated Learning	CodeCode Available	1
Time Series Anomaly Detection for Cyber-Physical Systems via Neural System Identification and Bayesian Filtering	Jun 15, 2021	Anomaly DetectionTime Series	CodeCode Available	1
Next Generation Reservoir Computing	Jun 14, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series	Jun 13, 2021	Anomaly DetectionGraph Neural Network	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