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cs.LG2026
Variational Learning of Disentangled Representations
Yuli Slavutsky, Ozgur Beker, David Blei +1
Disentangled representations separate factors that are shared across conditions from those that are condition-specific. Such separation is needed for generalization to new domains,…
cs.LG2024
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
Sebastian Salazar, Michal Kucer, Yixin Wang +2
This paper introduces posterior mean matching (PMM), a new method for generative modeling that is grounded in Bayesian inference. PMM uses conjugate pairs of distributions to model…