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Found 5 papers, 0 papers with code
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis
Given that the MLu performance relies on accurately approximating the conditional distributions, we focus on devising a synthetic data generation method based on conditional distribution estimation.
Improving SMOTE via Fusing Conditional VAE for Data-adaptive Noise Filtering
We investigate the problem of the generative model for imbalanced classification and introduce a framework to enhance the SMOTE algorithm using Variational Autoencoders (VAE).
Unicorn: U-Net for Sea Ice Forecasting with Convolutional Neural Ordinary Differential Equations
Sea ice at the North Pole is vital to global climate dynamics.
Balanced Marginal and Joint Distributional Learning via Mixture Cramer-Wold Distance
This measure enables us to capture both marginal and joint distributional information simultaneously, as it incorporates a mixture measure with point masses on standard basis vectors.
Uniform Pessimistic Risk and its Optimal Portfolio
However, estimating an optimal portfolio assessed by a pessimistic risk is still challenging due to the absence of a computationally tractable model.
