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cs.LG2026
From Graphs to Feeders: Constraint-Guided Diffusion for Rule-Compliant Feeder Generation
Yu Qin, Andrew Glaws, Aadil Latif +1
Generative modeling approaches often focus on recovering broad statistical characteristics from the training data. In the context of graph generation, this may refer to degree dist…
cs.LG2021
GANISP: a GAN-assisted Importance SPlitting Probability Estimator
Malik Hassanaly, Andrew Glaws, Ryan N. King
Designing manufacturing processes with high yield and strong reliability relies on effective methods for rare event estimation. Genealogical importance splitting reduces the varian…