129 citations · 586 across the 26 of their papers we have counts for
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cs.LG2022★ 15 cited
Using Machine Learning to Reduce Observational Biases When Detecting New Impacts on Mars
Kiri L. Wagstaff, Ingrid J. Daubar, Gary Doran +5
The current inventory of recent (fresh) impacts on Mars shows a strong bias towards areas of low thermal inertia. These areas are generally visually bright, and impacts create dark…
cs.LG2022
Hidden Heterogeneity: When to Choose Similarity-Based Calibration
Kiri L. Wagstaff, Thomas G. Dietterich
Trustworthy classifiers are essential to the adoption of machine learning predictions in many real-world settings. The predicted probability of possible outcomes can inform high-st…