4 papers
From Simulated Fluids to Living Tissue: Zero-Shot Foundation Model Transfer to Perturbed Embryos
Louisa Cornelis, Haewon Jeong, Irina Espejo +1
Morphogenesis is driven by the interplay of genetic regulation and tissue mechanics. In vivo video data is limited, particularly under genetic mutations and environmental perturbat…
Does Privacy Always Harm Fairness? Data-Dependent Trade-offs via Chernoff Information Neural Estimation
Arjun Nichani, Hsiang Hsu, Chun-Fu +2
Fairness and privacy are two vital pillars of trustworthy machine learning. Despite extensive research on these individual topics, their relationship has received significantly les…
Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images
Tian Qiu, Arjun Nichani, Rasta Tadayontahmasebi +1
Neural compression methods are gaining popularity due to their superior rate-distortion performance over traditional methods, even at extremely low bitrates below 0.1 bpp. As deep…
When Machine Learning Gets Personal: Evaluating Prediction and Explanation
Louisa Cornelis, Guillermo Bernárdez, Haewon Jeong +1
In high-stakes domains like healthcare, users often expect that sharing personal information with machine learning systems will yield tangible benefits, such as more accurate diagn…