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Existence and uniqueness of global in time measure solution for the multidimensional aggregation equation is analyzed. Such a system can be written as a continuity equation with a velocity field computed through a self-consistent…

Analysis of PDEs · Mathematics 2025-05-16 José Antonio Carrillo , Francois James , Frédéric Lagoutière , Nicolas Vauchelet

We prove the equivalence of the curvature-dimension bounds of Lott-Sturm-Villani (via entropy and optimal transport) and of Bakry--\'Emery (via energy and \Gamma_2$-calculus) in complete generality for infinitesimally Hilbertian metric…

Differential Geometry · Mathematics 2013-07-30 Matthias Erbar , Kazumasa Kuwada , Karl-Theodor Sturm

A recurring obstacle in the study of Wasserstein gradient flow is the lack of convexity of the square Wasserstein metric. In this paper, we develop a class of transport metrics that have better convexity properties and use these metrics to…

Analysis of PDEs · Mathematics 2014-06-06 Katy Craig

The symplectic vortex equations admit a variational description as global minimum of the Yang-Mills-Higgs functional. We study its negative gradient flow on holomorphic pairs $(A,u)$ where $A$ is a connection on a principal $G$-bundle $P$…

Differential Geometry · Mathematics 2018-01-11 Samuel Trautwein

The Stein Variational Gradient Descent method is a variational inference method in statistics that has recently received a lot of attention. The method provides a deterministic approximation of the target distribution, by introducing a…

Analysis of PDEs · Mathematics 2024-12-16 José A. Carrillo , Jakub Skrzeczkowski , Jethro Warnett

We prove that the standard gradient flow in parameter space that underlies many training algorithms in deep learning can be continuously deformed into an adapted gradient flow which yields (constrained) Euclidean gradient flow in output…

Machine Learning · Computer Science 2026-02-02 Thomas Chen , Patrícia Muñoz Ewald

We analyze gradient flows with jumps generated by a finite set of complete vector fields in involution using some Radon measures $u\in \mathcal{U}_a$ as admissible perturbations. Both the evolution of a bounded gradient flow $\{x^u(t,\l)\in…

Analysis of PDEs · Mathematics 2012-03-09 Saima Parveen , Constantin Varsan

We study the problem of convergence of the normalized Ricci flow evolving on a compact manifold $\Omega$ without boundary. In \cite{KS10, KS15} we derived, via PDE techniques, global-in-time existence of the classical solution and…

Differential Geometry · Mathematics 2021-01-15 Nikos I. Kavallaris , Takashi Suzuki

We propose a fully discrete variational scheme for nonlinear evolution equations with gradient flow structure on the space of finite Radon measures on an interval with respect to a generalized version of the Wasserstein distance with…

Numerical Analysis · Mathematics 2016-09-29 Jonathan Zinsl , Daniel Matthes

For addressing optimisation tasks on finite dimensional quantum systems, we give a comprehensive account of the foundations of gradient flows on Riemannian manifolds including new developments: we extend former results from Lie groups such…

Quantum Physics · Physics 2010-12-07 T. Schulte-Herbrueggen , S. J. Glaser , G. Dirr , U. Helmke

We show the equivalences of several notions of entropy, like a version of the topological entropy of the geodesic flow and the Minkowski dimension of the boundary, in metric spaces with convex geodesic bicombings satisfying a uniform…

Dynamical Systems · Mathematics 2021-05-26 Nicola Cavallucci

We study first order methods to compute the barycenter of a probability distribution $P$ over the space of probability measures with finite second moment. We develop a framework to derive global rates of convergence for both gradient…

Statistics Theory · Mathematics 2020-06-16 Sinho Chewi , Tyler Maunu , Philippe Rigollet , Austin J. Stromme

We formulate a trajectorial version of the relative entropy dissipation identity for McKean$-$Vlasov diffusions, extending the results of the papers [FJ16,KST20a], which apply to non-interacting diffusions. Our stochastic analysis approach…

Probability · Mathematics 2021-05-27 Bertram Tschiderer , Lane Chun Yeung

We develop a dynamical method for proving the sharp Berezin-Li-Yau inequality. The approach is based on the volume-preserving mean curvature flow and a new monotonicity principle for the Riesz mean $R_\Lambda(\Omega_t)$. For convex domains…

Differential Geometry · Mathematics 2026-05-26 Anton Alexa

We prove the well-posedness of entropy solutions for a wide class of nonlocal transport equations with nonlinear mobility in one spatial dimension. The solution is obtained as the limit of approximations constructed via a deterministic…

Analysis of PDEs · Mathematics 2025-09-25 Simone Fagioli , Oliver Tse

In this paper, we study the {\L}ojasiewicz-Simon gradient inequality for the mathematical model of grain boundary motion. We first derive a curve shortening equation with time-dependent mobility, which guarantees the energy dissipation law…

Analysis of PDEs · Mathematics 2026-03-24 Masashi Mizuno , Ayumi Sakiyama , Keisuke Takasao

We prove several abstract versions of the Lojasiewicz-Simon gradient inequality for an analytic functional on a Banach space that generalize previous abstract versions of this inequality, weakening their hypotheses and, in particular, the…

Differential Geometry · Mathematics 2020-08-17 Paul M. N. Feehan , Manousos Maridakis

In this paper we study the singular vanishing-viscosity limit of a gradient flow in a finite dimensional Hilbert space, focusing on the so-called delayed loss of stability of stationary solutions. We find a class of time-dependent energy…

Analysis of PDEs · Mathematics 2017-09-05 Giovanni Scilla , Francesco Solombrino

We propose to use the {\L}ojasiewicz inequality as a general tool for analyzing the convergence rate of gradient descent on a Hilbert manifold, without resorting to the continuous gradient flow. Using this tool, we show that a Sobolev…

Numerical Analysis · Mathematics 2021-05-21 Ziyun Zhang

Gromov-Wasserstein (GW) is a powerful tool to compare probability measures whose supports are in different metric spaces. GW suffers however from a computational drawback since it requires to solve a complex non-convex quadratic program. We…

Machine Learning · Statistics 2020-06-18 Tam Le , Nhat Ho , Makoto Yamada
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