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cs.LG2024
Rethinking Disentanglement under Dependent Factors of Variation
Antonio Almudévar, Alfonso Ortega
Representation learning is an approach that allows to discover and extract the factors of variation from the data. Intuitively, a representation is said to be disentangled if it se…
cs.LG2024
Predefined Prototypes for Intra-Class Separation and Disentanglement
Antonio Almudévar, Théo Mariotte, Alfonso Ortega +4
Prototypical Learning is based on the idea that there is a point (which we call prototype) around which the embeddings of a class are clustered. It has shown promising results in s…