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Showing 3351–3375 of 9169 papers

TitleStatusHype
Beam Prediction based on Large Language Models—0
Factor-augmented sparse MIDAS regressions with an application to nowcasting—0
AI-Powered Predictions for Electricity Load in Prosumer Communities—0
Adaptive Forecasting of Non-Stationary Nonlinear Time Series Based on the Evolving Weighted Neuro-Neo-Fuzzy-ANARX-Model—0
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series—0
Factor Network Autoregressions—0
Fading of collective attention shapes the evolution of linguistic variants—0
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting—0
A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs—0
Development and Evaluation of Recurrent Neural Network based Models for Hourly Traffic Volume and AADT Prediction—0
Fairness Hub Technical Briefs: Definition and Detection of Distribution Shift—0
Fairness in Forecasting and Learning Linear Dynamical Systems—0
Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces—0
Deterministic Reservoir Computing for Chaotic Time Series Prediction—0
Determining the Optimal Number of Clusters for Time Series Datasets with Symbolic Pattern Forest—0
Applying Regression Conformal Prediction with Nearest Neighbors to time series data—0
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference—0
FAR-Trans: An Investment Dataset for Financial Asset Recommendation—0
BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data—0
Fast Active Set Methods for Online Spike Inference from Calcium Imaging—0
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data—0
Classifiers With a Reject Option for Early Time-Series Classification—0
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations—0
Fast and interpretable electricity consumption scenario generation for individual consumers—0
Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19—0
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