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cs.LG2022
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors
Chester Holtz, Gal Mishne, Alexander Cloninger
Probabilistic generative models provide a flexible and systematic framework for learning the underlying geometry of data. However, model selection in this setting is challenging, p…
math.ST2022★ 1 cited
Supervised learning of sheared distributions using linearized optimal transport
Varun Khurana, Harish Kannan, Alexander Cloninger +1
In this paper we study supervised learning tasks on the space of probability measures. We approach this problem by embedding the space of probability measures into spaces usi…