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stat.ML2020★ 4 cited
Learning Flat Latent Manifolds with VAEs
Nutan Chen, Alexej Klushyn, Francesco Ferroni +2
Measuring the similarity between data points often requires domain knowledge, which can in parts be compensated by relying on unsupervised methods such as latent-variable models, w…
stat.ML2018★ 2 cited
Fast Approximate Geodesics for Deep Generative Models
Nutan Chen, Francesco Ferroni, Alexej Klushyn +3
The length of the geodesic between two data points along a Riemannian manifold, induced by a deep generative model, yields a principled measure of similarity. Current approaches ar…