International audienceIn this article we set up a splitting variant of the JKO scheme in order to handle gradient flows with respect to the Kantorovich-Fisher-Rao metric , recently introduced and defined on the space of positive Radon measure with varying masses. We perform successively a time step for the quadratic Wasserstein/Monge-Kantorovich distance, and then for the Hellinger/Fisher-Rao distance. Exploiting some inf-convolution structure of the metric we show convergence of the whole process for the standard class of energy functionals under suitable compactness assumptions, and investigate in details the case of internal energies. The interest is double: On the one hand we prove existence of weak solutions for a certain class of reac...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceWe analyze some parabolic PDEs with different drift terms which are gradient f...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceIn this article we set up a splitting variant of the JKO scheme in order to ha...
We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qu...
We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qu...
A wide range of diffusion equations can be interpreted as gradient flow with respect to Wasserstein ...
peer reviewedIn this paper, we show that unbalanced optimal transport provides a convenient framewor...
In this paper, we start from a very natural system of cross-diffusion equations, which can be seen a...
This article presents a new class of "optimal transportation"-like distances between arbitrary posit...
Gradient flows in the Wasserstein space have become a powerful tool in the analysis of diffusion equ...
In this paper, we start from a very natural system of cross-diffusion equations, which can be seen a...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceWe analyze some parabolic PDEs with different drift terms which are gradient f...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceWe analyze some parabolic PDEs with different drift terms which are gradient f...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceIn this article we set up a splitting variant of the JKO scheme in order to ha...
We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qu...
We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qu...
A wide range of diffusion equations can be interpreted as gradient flow with respect to Wasserstein ...
peer reviewedIn this paper, we show that unbalanced optimal transport provides a convenient framewor...
In this paper, we start from a very natural system of cross-diffusion equations, which can be seen a...
This article presents a new class of "optimal transportation"-like distances between arbitrary posit...
Gradient flows in the Wasserstein space have become a powerful tool in the analysis of diffusion equ...
In this paper, we start from a very natural system of cross-diffusion equations, which can be seen a...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceWe analyze some parabolic PDEs with different drift terms which are gradient f...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...
International audienceWe analyze some parabolic PDEs with different drift terms which are gradient f...
Published in Transactions on Machine Learning Research (November 2022)Minimizing functionals in the ...