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20242026
most citedA unified framework for evaluating the robustness of machine-learning interpretability for prospect risking

5 citations · 5 across the 4 of their papers we have counts for

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cs.CV2025

A Large-scale Benchmark on Geological Fault Delineation Models: Domain Shift, Training Dynamics, Generalizability, Evaluation and Inferential Behavior

Jorge Quesada, Chen Zhou, Prithwijit Chowdhury +5

Machine learning has taken a critical role in seismic interpretation workflows, especially in fault delineation tasks. However, despite the recent proliferation of pretrained model…