Google Scholar, arXiv
ML=Machine Learning, BI=Biological Imaging

[ML] Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations
Olawale Salaudeen, Oluwasanmi Koyejo.
arXiv, 2022

[ML] Adapting to Latent Subgroup Shifts via Concepts and Proxies
Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D’Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai.
Authors listed in alphabetical order
The International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.

[ML] Exploiting Causal Chains for Domain Generalization
Olawale Salaudeen, Oluwasanmi Koyejo.
Conference on Neural Information Processing Systems (NeurIPS), 2021. Workshop on Distribution Shifts – Connecting Methods and Applications (DistShift)
[paper] [poster]


[ML] Addressing Observational Biases in Algorithmic Fairness Assessments
Chirag Nagpal, Olawale Salaudeen, Sanmi Koyejo, Stephen Pfohl.
Conference on Neural Information Processing Systems (NeurIPS), 2022. Workshop on Algorithmic Fairness through the Lens of Causality and Privacy (extended abstract)

[BI] Ultra-fast 3D fMRI to explore cardiac-induced fluctuations in BOLD-based functional imaging
Brad Sutton, Aaron Anderson, Benjamin Zimmerman, Paul Camacho, Riwei Jin, Charles Marchini, Olawale Salaudeen, Natalie Ramsy, Davide Boido, Serge Charpak, Andrew Webb, Luisa Ciobanu.
International Society for Magnetic Resonance in Medicine (ISMRM), 2022 (abstract)