11 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.LG2026
In-context learning enables continental-scale subsurface temperature prediction from sparse local observations
Daniel O'Malley, Christopher W. Johnson, Javier E. Santos +10
Continental-scale knowledge of subsurface temperature is limited by the cost and sparsity of borehole measurements, but such information is essential for geothermal resource assess…
cs.LG2017★ 11 cited
Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm
Youzuo Lin, Shusen Wang, Jayaraman Thiagarajan +2
Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency, and subjective human factors. We…