Concept-based model explanations for electronic health records. - Diana Mincu; Eric Loreaux; Shaobo Hou; Sebastien Baur; Ivan Protsyuk; Martin Seneviratne; Anne Mottram; Nenad Tomasev; Alan Karthikesalingam; Jessica Schrouff (CHIL, 2021)

Best of both worlds: local and global explanations with human-understandable concepts. - Jessica Schrouff; Sebastien Baur; Shaobo Hou; Diana Mincu; Eric Loreaux; Ralph Blanes; James Wexler; Alan Karthikesalingam; Been Kim (CoRR, 2021)

Multitask prediction of organ dysfunction in the intensive care unit using sequential subnetwork routing. - Subhrajit Roy; Diana Mincu; Eric Loreaux; Anne Mottram; Ivan Protsyuk; Natalie Harris; Yuan Xue; Jessica Schrouff; Hugh Montgomery; Alistair Connell; Nenad Tomasev; Alan Karthikesalingam; et al. (J. Am. Medical Informatics Assoc., 2021)

Disability prediction in multiple sclerosis using performance outcome measures and demographic data. - Subhrajit Roy; Diana Mincu; Lev Proleev; Negar Rostamzadeh; Chintan Ghate; Natalie Harris; Christina Chen; Jessica Schrouff; Nenad Tomasev; Fletcher Lee Hartsell; Katherine A. Heller (CHIL, 2022)

Healthsheet: Development of a Transparency Artifact for Health Datasets. - Negar Rostamzadeh; Diana Mincu; Subhrajit Roy; Andrew Smart; Lauren Wilcox; Mahima Pushkarna; Jessica Schrouff; Razvan Amironesei; Nyalleng Moorosi; Katherine A. Heller (FAccT, 2022)

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. - Jessica Schrouff; Natalie Harris; Sanmi Koyejo; Ibrahim M. Alabdulmohsin; Eva Schnider; Krista Opsahl-Ong; Alexander Brown; Subhrajit Roy; Diana Mincu; Christina Chen; Awa Dieng; Yuan Liu; et al. (NeurIPS, 2022)

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? - Jessica Schrouff; Natalie Harris; Oluwasanmi Koyejo; Ibrahim Alabdulmohsin; Eva Schnider; Krista Opsahl-Ong; Alexander Brown; Subhrajit Roy; Diana Mincu; Christina Chen; Awa Dieng; Yuan Liu; et al. (CoRR, 2022)

Underspecification Presents Challenges for Credibility in Modern Machine Learning. - Alexander D'Amour; Katherine A. Heller; Dan Moldovan; Ben Adlam; Babak Alipanahi; Alex Beutel; Christina Chen; Jonathan Deaton; Jacob Eisenstein; Matthew D. Hoffman; Farhad Hormozdiari; Neil Houlsby; et al. (J. Mach. Learn. Res., 2022)

Developing robust benchmarks for driving forward AI innovation in healthcare. - Diana Mincu; Subhrajit Roy (Nat. Mac. Intell., 2022)

Longitudinal Modeling of Multiple Sclerosis using Continuous Time Models. - Alexander Norcliffe; Lev Proleev; Diana Mincu; Fletcher Lee Hartsell; Katherine A. Heller; Subhrajit Roy (CoRR, 2023)

STUDY: Socially Aware Temporally Casual Decoder Recommender Systems. - Eltayeb Ahmed; Diana Mincu; Lauren Harrell; Katherine A. Heller; Subhrajit Roy (CoRR, 2023)

Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression. - Alexander Luke Ian Norcliffe; Lev Proleev; Diana Mincu; Fletcher Lee Hartsell; Katherine A. Heller; Subhrajit Roy (Trans. Mach. Learn. Res., 2023)

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering. - Han Zhou 010; Xingchen Wan; Lev Proleev; Diana Mincu; Jilin Chen; Katherine A. Heller; Subhrajit Roy (ICLR, 2024)

Anniversary AI reflections. - Noelia Ferruz; Marinka Zitnik; Pierre-Yves Oudeyer; Emmie Hine; Nandana Sengupta; Yiyu Shi 001; Diana Mincu; Sebastian Porsdam Mann; Payel Das; Francesco Stella (Nat. Mac. Intell., 2024)