35 citations · 135 across the 17 of their papers we have counts for
17 papers
Categorical and geometric methods in statistical, manifold, and machine learning
Hông Vân Lê, Hà Quang Minh, Frederic Protin +1
We present and discuss applications of the category of probabilistic morphisms, initially developed in \cite{Le2023}, as well as some geometric methods to several classes of proble…
A cohomology-based Gromov-Hausdorff metric approach for quantifying molecular similarity
JunJie Wee, Xue Gong, Wilderich Tuschmann +1
We introduce, for the first time, a cohomology-based Gromov-Hausdorff ultrametric method to analyze 1-dimensional and higher-dimensional (co)homology groups, focusing on loops, voi…
Unified modelling of epidemics by coupled dynamics via Monte-Carlo Markov Chain algorithms
Frédéric Protin, Martel Jules, Duc Thang Nguyen +9
To forecast the time dynamics of an epidemic, we propose a discrete stochastic model that unifies and generalizes previous approaches to the subject. Viewing a given population of…
Epidemic Dynamics via Wavelet Theory and Machine Learning, with Applications to Covid-19
Tô Tat Dat, Protin Frédéric, Nguyen T. T. Hang +8
We introduce the concept of epidemic-fitted wavelets which comprise, in particular, as special cases the number of infectious individuals at time in classical SIR models…
Stability of the Cut Locus and a Central Limit Theorem for Fréchet Means of Riemannian Manifolds
Benjamin Eltzner, Fernando Galaz-Garcia, Stephan F. Huckemann +1
We obtain a Central Limit Theorem for closed Riemannian manifolds, clarifying along the way the geometric meaning of some of the hypotheses in Bhattacharya and Lin's Omnibus Centra…
On the topology of moduli spaces of non-negatively curved Riemannian metrics
Wilderich Tuschmann, Michael Wiemeler
We study spaces and moduli spaces of Riemannian metrics with non-negative Ricci or non-negative sectional curvature on closed and open manifolds. We construct, in particular, the f…