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 751–760 of 6748 papers

Title	Date	Tasks	Status	Hype
Calibration of Google Trends Time Series	Jul 27, 2020	Time SeriesTime Series Analysis	CodeCode Available	1
Can Multimodal LLMs Perform Time Series Anomaly Detection?	Feb 25, 2025	Anomaly DetectionIrregular Time Series	CodeCode Available	1
Multi-module Recurrent Convolutional Neural Network with Transformer Encoder for ECG Arrhythmia Classification	Aug 1, 2021	Time SeriesTime Series Analysis	CodeCode Available	1
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	Anomaly DetectionTime Series	CodeCode Available	1
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications	Jun 17, 2022	EEGElectroencephalogram (EEG)	CodeCode Available	1
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data	May 22, 2020	Domain AdaptationTime Series	CodeCode Available	1
Multi-step-ahead Stock Price Prediction Using Recurrent Fuzzy Neural Network and Variational Mode Decomposition	Dec 24, 2022	PredictionStock Price Prediction	CodeCode Available	1
Multitask learning and benchmarking with clinical time series data	Mar 22, 2017	BenchmarkingBIG-bench Machine Learning	CodeCode Available	1
A Deep Learning Approach to Analyzing Continuous-Time Systems	Sep 25, 2022	Deep LearningTime Series	CodeCode Available	1
BolT: Fused Window Transformers for fMRI Time Series Analysis	May 23, 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