Pith. sign in

REVIEW 1 cited by

Variational Modelling: Energies, gradient flows, and large deviations

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1402.1990 v1 pith:3DJ3DT7M submitted 2014-02-09 math-ph math.DSmath.MP

classification math-phmath.DSmath.MP
keywords modellingmethodologynotesvariationaldescribediffusionexplainlarge
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

These are lecture notes for various Summer and Winter schools that I have given. The notes describe the methodology called Variational Modelling, and focus on the application to the modelling of gradient-flow systems. I describe the methodology itself in great detail, and explain why this is a rational modelling route. A central example is diffusion, in combination with various other processes, and a large part of the notes are devoted to this phenomenon. In the Variational Modelling methodology, diffusion is commonly modelled by including entropic terms in the driving functional and Wasserstein-type terms in the dissipation. I explain how to understand these objects, motivate them from more basic models, and how to use them in new situations.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Nonlocal Onsager Operators and Entropy Dissipation for Finite-State Schr\"odinger Bridges

    math.OC 2026-06 unverdicted novelty 6.0 of 10

    Develops nonlocal Onsager operators for terminal marginal evolution in finite-state Schrödinger bridges as gradient flows of relative entropy, with global well-posedness and convergence proved under positivity assumptions.

Pith tools