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R. Cont

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Preprint Jul 2026

Mimicking diffusion processes with differential equations

The probability-flow ordinary differential equation (PF-ODE) associated with a diffusion process is widely used in score-based generative modeling as a deterministic sampler that reproduces the marginal distributions of the diffusion. The validity of this marginal-matching property depends on the well-posedness of an ordinary differential equation whose velocity field is constructed from the score function of the diffusion. We examine the precise mathematical relation between a diffusion process, the Fokker-Planck equation and the associated PF-ODE under weak regularity assumptions on the drift and score. We establish existence and uniqueness of the marginal density flow as a solution of the Fokker--Planck equation under minimal regularity assumptions. We then study the corresponding Lagrangian problem using the DiPerna-Lions-Ambrosio theory of regular Lagrangian flows. We prove existence, uniqueness and stability of the flow, and show that it transports the initial distribution onto the diffusion marginals, under Sobolev or bounded-variation regularity of the score together with one-sided bounds on the divergence of the probability-flow velocity. We identify sufficient conditions for the required regularity in diffusion models relevant for applications. Our analysis underlines a fundamental distinction between Eulerian and Lagrangian descriptions. We construct a counterexample in which the Fokker--Planck equation has a unique density flow while the associated PF-ODE fails to admit a regular Lagrangian flow from the initial time, demonstrating that uniqueness of the density evolution does not in general imply the existence of a deterministic probability-flow representation. Finally, we derive stability estimates for probability-flow trajectories under learned score approximations. Our findings have implications for the training and deployment of score-based diffusion models.

R. Cont · 1 citation

Preprint Aug 2026

Higher-order variation and pathwise Ito calculus on manifolds

We develop an intrinsic calculus for smooth functions of paths of arbitrarily low regularity on smooth manifolds. The regularity of paths is defined in terms of a $p$-th variation tensor along a sequence of partitions, for an arbitrary integer $p$; this tensor is constructed as a local symmetric tensor measure along the path. We define pathwise integrals of closed one-forms along paths with finite $p$-th variation and derive a change of variable formula for smooth functions of such paths. For $p=2$, our results give a manifold version of H. F\"ollmer's pathwise It\^o calculus. Our construction only requires an affine connection on the manifold and may be viewed as a higher-order analogue of L. Schwartz's second-order differential geometry. The connection provides a splitting of higher-order tangent vectors into symmetric tensor components and leads to a geometric transfer principle: the change-of-variable formula defines an intrinsic, connection-independent functional of the reduced $p$-jet of the test function, whose canonical highest-order component is determined by the $p$-th variation tensor. Although our results are purely geometric, they apply to manifold-valued stochastic processes with highly irregular paths and yield a higher-order It\^o-type calculus for such processes. We illustrate this calculus for exponential lifts of fractional Brownian motions to Riemannian manifolds and Lie groups.

R. Cont · 0 citations