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Contrastive learning

Dr Melanie Weber



Contrastive learning seeks to train a representation function that encodes the similarity structure in a data set based on pairs of positive samples (similar data points) and negative samples (dissimilar data points). This project will investigate ways of incorporating geometric information, such as equivariances or symmetries, into Contrastive Learning approaches. Depending on the interests and expertise of the group, both computational and theoretical avenues of investigation may be pursued.

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