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Found 5 papers, 3 papers with code
Learning Nonparametric High-Dimensional Generative Models: The Empirical-Beta-Copula Autoencoder
By sampling from the latent space of an autoencoder and decoding the latent space samples to the original data space, any autoencoder can simply be turned into a generative model.
A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling
The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape.
Enhancing Energy System Models Using Better Load Forecasts
These biases and high errors affect the quality of energy system models.
From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting
Modeling price risks is crucial for economic decision making in energy markets.
Signing the Supermask: Keep, Hide, Invert
Through this extension and adaptations of initialization methods, we achieve a pruning rate of up to 99%, while still matching or exceeding the performance of various baseline and previous models.
