Peter Ochs

Robust generative modeling is achieved by replacing squared error with geometric median regression in Flow Matching, outperforming standard methods under severe data contamination.

Algorithm unrolling's "curse" – initial Jacobian divergence – can be tamed by simply truncating early derivative iterations or using warm-starting in bilevel optimization.