A novel framework approximates unbalanced optimal transport using Neural ODEs via a generalized discrete problem, a Sinkhorn-inspired scheme with proven convergence and error estimates, and derived transport dynamics.
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Control, Optimal Transport and Neural Differential Equations in Supervised Learning
A novel framework approximates unbalanced optimal transport using Neural ODEs via a generalized discrete problem, a Sinkhorn-inspired scheme with proven convergence and error estimates, and derived transport dynamics.
- Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations