2 papers
cs.LG2026
Process-Guided Concept Bottleneck Model
Reza M. Asiyabi, SEOSAW Partnership, Steven Hancock +1
Concept Bottleneck Models (CBMs) improve the explainability of black-box Deep Learning (DL) by introducing intermediate semantic concepts. However, standard CBMs often overlook dom…
cs.LG2024
UFLUX v2.0: A Process-Informed Machine Learning Framework for Efficient and Explainable Modelling of Terrestrial Carbon Uptake
Wenquan Dong, Songyan Zhu, Jian Xu +6
Gross Primary Productivity (GPP), the amount of carbon plants fixed by photosynthesis, is pivotal for understanding the global carbon cycle and ecosystem functioning. Process-based…