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cs.LG2026
Generative Inverse Design with Abstention via Diagonal Flow Matching
Miguel de Campos, Werner Krebs, Hanno Gottschalk
Inverse design aims to find design parameters achieving target performance . Generative approaches learn bidirectional mappings between designs and labels, enabling divers…
cs.LG2026
How well do generative models solve inverse problems? A benchmark study
Patrick Krüger, Patrick Materne, Werner Krebs +1
Generative learning generates high dimensional data based on low dimensional conditions, also called prompts. Therefore, generative learning algorithms are eligible for solving (Ba…