arXiv Statistics ML
Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing
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Aug 12
A Local Sinkhorn Framework for Conditional Distribution Reconstruction of Multidimensional Random Fields
In this paper, we propose a local Sinkhorn divergence framework for conditional distribution reconstruction of multidimensional random fields. By utilizing the debiased Sinkhorn divergence, our proposed approach develops a differentiable and computationally efficient local distribution matching objective to train stochastic neural networks (SNNs).