Identifying Bias in Data Using Two-Distribution Hypothesis Tests. - William Yik; Limnanthes Serafini; Timothy Lindsey; George D. Montañez (AIES, 2022)

Exploring Randomly Wired Neural Networks for Climate Model Emulation. - William Yik; Sam J. Silva; Andrew Geiss; Duncan Watson-Parris (CoRR, 2022)

Finite-Sample Bounds for Two-Distribution Hypothesis Tests. - Cynthia Hom; William Yik; George D. Montañez (DSAA, 2023)

Southern Ocean Dynamics Under Climate Change: New Knowledge Through Physics-Guided Machine Learning. - William Yik; Maike Sonnewald; Mariana C. A. Clare; Redouane Lguensat (CoRR, 2023)

Enforcing Equity in Neural Climate Emulators. - William Yik; Sam J. Silva (CoRR, 2024)