2 papers
cs.CV2026
StruMPL: Multi-task Dense Regression under Disjoint Partial Supervision and MNAR Labels
Reza M. Asiyabi, Juan Alberto Molina-Valero, The SEOSAW Partnership +2
Estimating forest aboveground biomass (AGB) from Earth observation combines two structurally incompatible label sources: spaceborne lidar provides canopy structure at millions of l…
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…