Research

Out-of-Distribution Learning

Out-of-Distribution learning is concerned with developing methods where the distribution of the data processed at test time may be different from the distrib...

Transfer Learning from Multiple Sources

Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the availab...

Publications