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 651–660 of 6748 papers

Title	Date	Tasks	Status	Hype
Predicting Patient Outcomes with Graph Representation Learning	Jan 11, 2021	Graph Representation LearningLength-of-Stay prediction	CodeCode Available	1
A Bayesian neural network predicts the dissolution of compact planetary systems	Jan 11, 2021	BIG-bench Machine LearningTime Series Analysis	CodeCode Available	1
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series	Jan 10, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading Rules	Jan 8, 2021	DecoderDeep Reinforcement Learning	CodeCode Available	1
Do We Really Need Deep Learning Models for Time Series Forecasting?	Jan 6, 2021	Deep Learningregression	CodeCode Available	1
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space	Jan 1, 2021	Data AugmentationTime Series	CodeCode Available	1
Interpretable Multivariate Time Series Forecasting with Temporal Attention Convolutional Neural Networks	Jan 1, 2021	Multivariate Time Series ForecastingTime Series	CodeCode Available	1
Ensembles of Localised Models for Time Series Forecasting	Dec 30, 2020	ClusteringTime Series	CodeCode Available	1
Towards Automated Satellite Conjunction Management with Bayesian Deep Learning	Dec 23, 2020	Collision AvoidanceDeep Learning	CodeCode Available	1
Score Matched Neural Exponential Families for Likelihood-Free Inference	Dec 20, 2020	Bayesian InferenceTime Series	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