37 citations · 107 across the 19 of their papers we have counts for
22 papers
Choosing the parameter of the Fermat distance: navigating geometry and noise
Frédéric Chazal, Laure Ferraris, Pablo Groisman +3
The Fermat distance has been recently established as a useful tool for machine learning tasks when a natural distance is not directly available to the practitioner or to improve th…
The Kuramoto model on dynamic random graphs
Pablo Groisman, Ruojun Huang, Hernan Vivas
We propose a Kuramoto model of coupled oscillators on a time-varying graph, whose dynamics is dictated by a Markov process in the space of graphs. The simplest representative is co…
Intrinsic persistent homology via density-based metric learning
Ximena Fernández, Eugenio Borghini, Gabriel Mindlin +1
We address the problem of estimating topological features from data in high dimensional Euclidean spaces under the manifold assumption. Our approach is based on the computation of…
The quasi-stationary distribution of the subcritical contact process
Franco Arrejoría, Pablo Groisman, Leonardo T. Rolla
We show that the quasi-stationary distribution of the subcritical contact process on is unique. This is in contrast with other processes which also do not come down…
Tumor growth, -positivity, Multitype branching and Quasistationarity
Analía Ferrari, Pablo Groisman, Krishnamurthi Ravishankar
Motivated by tumor growth models we establish conditions for the positivity of Markov processes and positive matrices. We then apply them to obtain the asymptotic behavior of t…
F-KPP Scaling limit and selection principle for a Brunet-Derrida type particle system
Pablo Groisman, Matthieu Jonckheere, Julián Martínez
We study a particle system with the following diffusion-branching-selection mechanism. Particles perform independent one dimensional Brownian motions and on top of that, at a const…