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cs.LG2024
Stabilizing the Kumaraswamy Distribution
Max Wasserman, Gonzalo Mateos
Large-scale latent variable models require expressive continuous distributions that support efficient sampling and low-variance differentiation, achievable through the reparameteri…
cs.LG2024
Graph Structure Learning with Interpretable Bayesian Neural Networks
Max Wasserman, Gonzalo Mateos
Graphs serve as generic tools to encode the underlying relational structure of data. Often this graph is not given, and so the task of inferring it from nodal observations becomes…