SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–575 of 6748 papers

TitleStatusHype
Calibration of Google Trends Time SeriesCode1
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
BolT: Fused Window Transformers for fMRI Time Series AnalysisCode1
An Open Source and Reproducible Implementation of LSTM and GRU Networks for Time Series ForecastingCode1
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetCode1
Compatible deep neural network framework with financial time series data, including data preprocessor, neural network model and trading strategyCode1
The Signature Kernel is the solution of a Goursat PDECode1
Conformal Time-series ForecastingCode1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural NetworksCode1
AGNet: Weighing Black Holes with Deep LearningCode1
Construe: a software solution for the explanation-based interpretation of time seriesCode1
AGNet: Weighing Black Holes with Machine LearningCode1
Continuous-Time Deep Glioma Growth ModelsCode1
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-SeriesCode1
Contrastive Learning for Unsupervised Domain Adaptation of Time SeriesCode1
Convolution-enhanced Evolving Attention NetworksCode1
Copula Conformal Prediction for Multi-step Time Series ForecastingCode1
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG ClassificationCode1
Cost-effective Interactive Attention Learning with Neural Attention ProcessesCode1
Counterfactual Explanations for Machine Learning on Multivariate Time Series DataCode1
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19Code1
CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact DataCode1
Crop Classification under Varying Cloud Cover with Neural Ordinary Differential EquationsCode1
Building an Automated and Self-Aware Anomaly Detection SystemCode1
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified