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 2501–2525 of 6748 papers

TitleStatusHype
Previsão dos preços de abertura, mínima e máxima de índices de mercados financeiros usando a associação de redes neurais LSTM—0
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-SeriesCode1
Analysis of complex circadian time series data using wavelets—0
Otimizacao de pesos e funcoes de ativacao de redes neurais aplicadas na previsao de series temporais—0
Inference in heavy-tailed non-stationary multivariate time series—0
Temporal Dependencies in Feature Importance for Time Series PredictionsCode1
Spatio-temporal graph neural networks for multi-site PV power forecasting—0
The interpretation of endobronchial ultrasound image using 3D convolutional neural network for differentiating malignant and benign mediastinal lesions—0
Demand Forecasting in Smart Grid Using Long Short-Term Memory—0
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries ChallengeCode0
Snippet Policy Network for Multi-class Varied-length ECG Early Classification—0
Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals—0
Vision-Guided Forecasting -- Visual Context for Multi-Horizon Time Series Forecasting—0
Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling—0
Inverse and Quanto Inverse Options in a Black-Scholes World—0
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale—0
A Signal Detection Scheme Based on Deep Learning in OFDM Systems—0
Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices—0
Automatic Detection Of Noise Events at Shooting Range Using Machine Learning—0
COVID-19 and the gig economy in PolandCode0
Generative adversarial networks in time series: A survey and taxonomyCode1
Heteroscedastic Temporal Variational Autoencoder For Irregular Time SeriesCode1
Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces—0
FNetAR: Mixing Tokens with Autoregressive Fourier TransformsCode0
Tsformer: Time series Transformer for tourism demand forecasting—0
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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