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Found 3 papers, 1 papers with code
Equivariant Representation Learning in the Presence of Stabilizers
We introduce Equivariant Isomorphic Networks (EquIN) -- a method for learning representations that are equivariant with respect to general group actions over data.
Identifying the Sources of Uncertainty in Object Classification
In image-based object classification, the visual appearance of objects determines which class they are assigned to.
Quantifying and Learning Disentangled Representations with Limited Supervision
Although several works focus on learning LSBD representations, such methods require supervision on the underlying transformations for the entire dataset, and cannot deal with unlabeled data.
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