337 citations · 512 across the 24 of their papers we have counts for
8 papers · 1 filter
SW-VAE: Weakly Supervised Learn Disentangled Representation Via Latent Factor Swapping
Jiageng Zhu, Hanchen Xie, Wael Abd-Almageed
Representation disentanglement is an important goal of representation learning that benefits various downstream tasks. To achieve this goal, many unsupervised learning representati…
Weakly Supervised Invariant Representation Learning Via Disentangling Known and Unknown Nuisance Factors
Jiageng Zhu, Hanchen Xie, Wael Abd-Almageed
Disentangled and invariant representations are two critical goals of representation learning and many approaches have been proposed to achieve either one of them. However, those tw…
CAT: Controllable Attribute Translation for Fair Facial Attribute Classification
Jiazhi Li, Wael Abd-Almageed
As the social impact of visual recognition has been under scrutiny, several protected-attribute balanced datasets emerged to address dataset bias in imbalanced datasets. However, i…
MONet: Multi-scale Overlap Network for Duplication Detection in Biomedical Images
Ekraam Sabir, Soumyaroop Nandi, Wael AbdAlmageed +1
Manipulation of biomedical images to misrepresent experimental results has plagued the biomedical community for a while. Recent interest in the problem led to the curation of a dat…
Learning Robust Representations Of Generative Models Using Set-Based Artificial Fingerprints
Hae Jin Song, Wael AbdAlmageed
With recent progress in deep generative models, the problem of identifying synthetic data and comparing their underlying generative processes has become an imperative task for vari…
Do-Operation Guided Causal Representation Learning with Reduced Supervision Strength
Jiageng Zhu, Hanchen Xie, Wael AbdAlmageed
Causal representation learning has been proposed to encode relationships between factors presented in the high dimensional data. However, existing methods suffer from merely using…