3 papers
cs.LG2026
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology
Ka Chun Lam, Francisco Pereira, Bridget W Mahony +1
Psychiatry research seeks to understand the manifestations of psychopathology in behavior, as measured in questionnaire data, by identifying a small number of latent factors that e…
cs.CV2026
Similarity-based representation factorization for revealing interpretable dimensions in representational data
Florian P. Mahner, Ka Chun Lam, Francisco Pereira +1
The study of representations is widespread across fields, including neuroscience, psychology, and artificial intelligence. While representations are often studied and compared thro…
cs.CV2026
Characterizing Universal Object Representations Across Vision Models
Florian P. Mahner, Johannes Roth, Ka Chun Lam +3
Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. However, what remains unknown…