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

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Showing 176–200 of 6748 papers

TitleStatusHype
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
CUTS: Neural Causal Discovery from Irregular Time-Series DataCode1
Deep ConvLSTM with self-attention for human activity decoding using wearablesCode1
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural NetworksCode1
Conformal prediction set for time-seriesCode1
Neural graphical modelling in continuous-time: consistency guarantees and algorithmsCode1
An Experimental Review on Deep Learning Architectures for Time Series ForecastingCode1
Conditional GAN for timeseries generationCode1
Exathlon: A Benchmark for Explainable Anomaly Detection over Time SeriesCode1
An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural NetworksCode1
The Signature Kernel is the solution of a Goursat PDECode1
Conditional Sig-Wasserstein GANs for Time Series GenerationCode1
A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking ApplicationsCode1
A Deep Learning Approach to Analyzing Continuous-Time SystemsCode1
Conformal Time-series ForecastingCode1
An Accurate and Fully-Automated Ensemble Model for Weekly Time Series ForecastingCode1
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time seriesCode1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent AutoencodersCode1
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG ClassificationCode1
Construe: a software solution for the explanation-based interpretation of time seriesCode1
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19Code1
An Open Source and Reproducible Implementation of LSTM and GRU Networks for Time Series ForecastingCode1
Convolutional Radio Modulation Recognition NetworksCode1
A Neural PDE Solver with Temporal Stencil ModelingCode1
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time SeriesCode1
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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