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 2501–2550 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
Temporal Dependencies in Feature Importance for Time Series PredictionsCode1
Otimizacao de pesos e funcoes de ativacao de redes neurais aplicadas na previsao de series temporais—0
Analysis of complex circadian time series data using wavelets—0
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-SeriesCode1
Inference in heavy-tailed non-stationary multivariate time series—0
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
Inverse and Quanto Inverse Options in a Black-Scholes World—0
Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling—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
Heteroscedastic Temporal Variational Autoencoder For Irregular Time SeriesCode1
Generative adversarial networks in time series: A survey and taxonomyCode1
Automatic Detection Of Noise Events at Shooting Range Using Machine Learning—0
COVID-19 and the gig economy in PolandCode0
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
Neural Ordinary Differential Equation Model for Evolutionary Subspace Clustering and Its Applications—0
Recovering lost and absent information in temporal networksCode0
A Framework for Imbalanced Time-series ForecastingCode0
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies—0
Multiple species animal movements: network properties, disease dynamic and the impact of targeted control actionsCode0
Adaptive Inducing Points Selection For Gaussian Processes—0
Improving COVID-19 Forecasting using eXogenous VariablesCode0
High-dimensional Multivariate Time Series Forecasting in IoT Applications using Embedding Non-stationary Fuzzy Time Series—0
Approximation Theory of Convolutional Architectures for Time Series Modelling—0
Predicting the 2020 US Presidential Election with Twitter—0
OnlineSTL: Scaling Time Series Decomposition by 100x—0
Topological Attention for Time Series Forecasting—0
Long-term series forecasting with Query Selector -- efficient model of sparse attentionCode1
Wave-based extreme deep learning based on non-linear time-Floquet entanglement—0
Stock price prediction using BERT and GAN—0
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
A Method for Estimating the Entropy of Time Series Using Artificial Neural Networks—0
STRODE: Stochastic Boundary Ordinary Differential EquationCode1
Time Series Anomaly Detection for Smart Grids: A Survey—0
Online Graph Topology Learning from Matrix-valued Time Series—0
Estimating covariant Lyapunov vectors from data—0
Neural Contextual Anomaly Detection for Time SeriesCode1
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention NetworksCode1
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty QuantificationCode1
Integrating LSTMs and GNNs for COVID-19 ForecastingCode1
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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