Geometric Pareto Control embeds Pareto solutions in a Lie group submanifold and navigates via Riemannian gradient flow to achieve 100% feasibility and low suboptimality in control tasks without retraining.
arXiv preprint arXiv:2601.09025 , year=
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An asymmetric two-pathway graph neural network architecture enables certified zero-shot transfer of inference across changing system topologies by anchoring latent geometry to operator spectra.
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Geometric Pareto Control: Riemannian Gradient Flow of Energy Function via Lie Group Homotopy
Geometric Pareto Control embeds Pareto solutions in a Lie group submanifold and navigates via Riemannian gradient flow to achieve 100% feasibility and low suboptimality in control tasks without retraining.