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cs.LG2024
Towards the Reusability and Compositionality of Causal Representations
Davide Talon, Phillip Lippe, Stuart James +2
Causal Representation Learning (CRL) aims at identifying high-level causal factors and their relationships from high-dimensional observations, e.g., images. While most CRL works fo…
cs.LG2023
Key Design Choices for Double-Transfer in Source-Free Unsupervised Domain Adaptation
Andrea Maracani, Raffaello Camoriano, Elisa Maiettini +3
Fine-tuning and Domain Adaptation emerged as effective strategies for efficiently transferring deep learning models to new target tasks. However, target domain labels are not acces…