GeoTopoDiff transfers diffusion priors to a mixed graph state space with topology-aware constraints from sparse slices, cutting morphology errors by 19.8% and transport errors by 36.5% on PTFE and sandstone samples.
Advances in Neural Information Processing Systems , volume=
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A single-objective rectified flow variant uses neural ODEs trained by regression to monotonically decrease a fixed convex transport cost while preserving marginal distributions.
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GeoTopoDiff: Learning Geometry--Topology Graph Priors through Boundary-Constrained Mixed Diffusion for Sparse-Slice 3D Porous Reconstruction
GeoTopoDiff transfers diffusion priors to a mixed graph state space with topology-aware constraints from sparse slices, cutting morphology errors by 19.8% and transport errors by 36.5% on PTFE and sandstone samples.
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Rectified Flow: A Marginal Preserving Approach to Optimal Transport
A single-objective rectified flow variant uses neural ODEs trained by regression to monotonically decrease a fixed convex transport cost while preserving marginal distributions.