A biased sparsity penalty in the neural OT minimax objective yields displacement-sparse maps, with an adaptive penalty schedule that outperforms fixed strengths on synthetic and real perturbation data.
Optimizing functionals on the space of probabilities with input convex neural networks
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Displacement-Sparse Neural Optimal Transport
A biased sparsity penalty in the neural OT minimax objective yields displacement-sparse maps, with an adaptive penalty schedule that outperforms fixed strengths on synthetic and real perturbation data.