Gaussian Wasserstein Inference: Gaussian Measures meet Bayesian Deep Learning
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The slides for a talk I gave about how we can use Gaussian Measures on the space of square-integrable functions to construct a highly flexible inference framework. We obtain state-of-the art results on benchmark data sets by combining deep neural networks with Gaussian measures in a novel way. The slides can be found here.