Hopf-Cole transformation via generalized Schr"odinger bridge problem
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Abstract (arXiv)
We study generalized Hopf-Cole transformations motivated by the Schr"odinger bridge problem, which can be seen as a boundary value Hamiltonian system on the Wasserstein space. We prove that generalized Hopf-Cole transformations are symplectic submersions in the Wasserstein symplectic geometry. Many examples, including a Hopf-Cole transformation for the shallow water equations, are given. Based on this transformation, energy splitting inequalities are provided.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Jan 2019.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 2; 2025: 1; 2026: 2.
8 papers.
- 2022An optimal control perspective on diffusion-based generative modelingcited by 147
- 2023A Computational Framework for Solving Wasserstein Lagrangian Flowscited by 46
- 2022Maximum Likelihood Training of Implicit Nonlinear Diffusion Modelscited by 42
- 2024Learning stochastic dynamics from snapshots through regularized unbalanced optimal transportcited by 33
- 2024HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative modelscited by 2
- 2026Stochastic Control Methods for Optimizationcited by 1
- 2026Nonlocal Mean Field Schr"odinger Bridge with Learned Interactionscited by 1
- 2025Contact Wasserstein Geodesics for Non-Conservative Schr"odinger Bridgescited by 0
- 2026Nonlocal Mean Field Schr"odinger Bridge with Learned Interactions2 Jun 2026
- 2026Stochastic Control Methods for Optimization3 Jan 2026
- 2025Contact Wasserstein Geodesics for Non-Conservative Schr"odinger Bridges10 Nov 2025
- 2024Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport1 Oct 2024
- 2024HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models15 Sep 2024
- 2023A Computational Framework for Solving Wasserstein Lagrangian Flows16 Oct 2023
- 2022An optimal control perspective on diffusion-based generative modeling2 Nov 2022
- 2022Maximum Likelihood Training of Implicit Nonlinear Diffusion Models27 May 2022