Taking advantage of the Benamou-Brenier dynamic formulation of optimal transport, we propose a convex formulation for each step of the JKO scheme for Wasserstein gradient flows which can be attacked by an augmented Lagrangian method which we call the ALG2-JKO scheme. We test the algorithm in particular on the porous medium equation. We also consider a semi implicit variant which enables us to treat nonlocal interactions as well as systems of interacting species. Regarding systems, we can also use the ALG2-JKO scheme for the simulation of crowd motion models with several species
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 ...
Gradient flows of energy functionals on the space of probability measures with Wasserstein metric ha...
Taking advantage of the Benamou-Brenier dynamic formulation of optimal transport, we propose a conve...
A wide range of diffusion equations can be interpreted as gradient flow with respect to Wasserstein ...
This chapter reviews different numerical methods for specific examples of Wasserstein gradient flows...
Starting from a motivation in the modeling of crowd movement, the paper presents the topics of gradi...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
International audienceWe study a model of crowd motion following a gradient vector field, with possi...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
Combining the classical theory of optimal transport with modern operator splitting techniques, we de...
International audienceThis article details a novel numerical scheme to approximate gradient flows fo...
Gradient flows in the Wasserstein space have become a powerful tool in the analysis of diffusion equ...
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 ...
Gradient flows of energy functionals on the space of probability measures with Wasserstein metric ha...
Taking advantage of the Benamou-Brenier dynamic formulation of optimal transport, we propose a conve...
A wide range of diffusion equations can be interpreted as gradient flow with respect to Wasserstein ...
This chapter reviews different numerical methods for specific examples of Wasserstein gradient flows...
Starting from a motivation in the modeling of crowd movement, the paper presents the topics of gradi...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
International audienceWe study a model of crowd motion following a gradient vector field, with possi...
We study a model of crowd motion following a gradient vector field, with possibly additional interac...
Combining the classical theory of optimal transport with modern operator splitting techniques, we de...
International audienceThis article details a novel numerical scheme to approximate gradient flows fo...
Gradient flows in the Wasserstein space have become a powerful tool in the analysis of diffusion equ...
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 ...
Gradient flows of energy functionals on the space of probability measures with Wasserstein metric ha...