Probabilistic Graph Neural Inference for circular manufacturing supply chains for extreme data sparsity scenarios

The author describes a eureka moment while modeling circular manufacturing supply chains using Graph Neural Networks in scenarios of extreme data sparsity. The key insight was to embrace the inherent uncertainty through probabilistic inference techniques, rather than trying to force more data into the system.