Rainbow Graphs and Switching Classes. - Suho Oh; Hwanchul Yoo; Taedong Yun (SIAM J. Discret. Math., 2013)

SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. - Steve Yadlowsky; Taedong Yun; Cory Y. McLean; Alexander D'Amour (NeurIPS, 2021)

Accurate, scalable cohort variant calls using DeepVariant and GLnexus. - Taedong Yun; Helen Li; Pi-Chuan Chang; Michael F. Lin; Andrew Carroll; Cory Y. McLean (Bioinform., 2021)

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)

Evaluating unsupervised disentangled representation learning for genomic discovery and disease risk prediction. - Taedong Yun (CoRR, 2023)

Improving variant calling using population data and deep learning. - Nae-Chyun Chen; Alexey Kolesnikov; Sidharth Goel; Taedong Yun; Pi-Chuan Chang; Andrew Carroll (BMC Bioinform., 2023)

Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions. - Taedong Yun; Eric Yang; Mustafa Safdari; Jong Ha Lee; Vaishnavi Vinod Kumar; S. Sara Mahdavi; Jonathan Amar; Derek Peyton; Reut Aharony; Andreas Michaelides; Logan Douglas Schneider; Isaac R. Galatzer-Levy; et al. (ACL (Findings), 2025)