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In microbiome studies, it is often of great interest to identify clusters or partitions of microbiome profiles within a study population and to characterize the distinctive attributes of each resulting microbial community. While raw counts…

Methodology · Statistics 2025-08-18 Zhongmao Liu , Xiaohui Yin , Yanjiao Zhou , Gen Li , Kun Chen

We study multi-parameters deformations of isolated singularity function-germs on either a subanalytic set or a complex analytic spaces. We prove that if such a deformation has no coalescing of singular points, then it has constant…

Complex Variables · Mathematics 2022-06-22 Aurélio Menegon , Miriam da Silva Pereira

We study a class of continuous deformations of branched complex projective structures on closed surfaces of genus $g\geq 2$, which preserve the holonomy representation of the structure and the order of the branch points. In the case of…

Complex Variables · Mathematics 2021-03-25 Stefano Francaviglia , Lorenzo Ruffoni

Kernel mean embeddings have recently attracted the attention of the machine learning community. They map measures $\mu$ from some set $M$ to functions in a reproducing kernel Hilbert space (RKHS) with kernel $k$. The RKHS distance of two…

Machine Learning · Statistics 2019-12-18 Carl-Johann Simon-Gabriel , Bernhard Schölkopf

Kernel mean embeddings are a popular tool that consists in representing probability measures by their infinite-dimensional mean embeddings in a reproducing kernel Hilbert space. When the kernel is characteristic, mean embeddings can be used…

Machine Learning · Computer Science 2021-06-29 Boris Muzellec , Francis Bach , Alessandro Rudi

This paper studies Schauder theory to transmission problems modelled by fully nonlinear uniformly elliptic equations of second order. We focus on operators F that fails to be concave or convex in the space of symmetric matrices. In a first…

Analysis of PDEs · Mathematics 2024-04-26 G. C. Ricarte , C. S. Barroso , L. S. Tavares

We present a general framework for studying harmonic analysis of functions in the settings of various emerging problems in the theory of diffusion geometry. The starting point of the now classical diffusion geometry approach is the…

Classical Analysis and ODEs · Mathematics 2016-07-18 Hrushikesh N. Mhaskar

Reparameterizable densities are an important way to learn probability distributions in a deep learning setting. For many distributions it is possible to create low-variance gradient estimators by utilizing a `reparameterization trick'. Due…

Machine Learning · Statistics 2019-03-13 Luca Falorsi , Pim de Haan , Tim R. Davidson , Patrick Forré

Effective methods are introduced for testing zero-dimensionality of varieties at a point. The motivation of this paper is to compute and analyze deformations of isolated hypersurface singularities. As an application, methods for computing…

Symbolic Computation · Computer Science 2019-04-01 Katsusuke Nabeshima , Shinichi Tajima

Identifying possible clusters in datasets and estimating their overall modularity are central tasks in pattern recognition. In the present work, concepts and methodologies are described for performing these tasks while considering only the…

Physics and Society · Physics 2026-05-27 Alexandre Benatti , Luciano da F. Costa

We study the Hadamard finite part of divergent integrals of differential forms with singularities on submanifolds. We give formulae for the dependence of the finite part on the choice of regularization and express them in terms of a…

Mathematical Physics · Physics 2016-11-17 Giovanni Felder , David Kazhdan

We extend the semigroup approach used in [23,21] to provide alternative proofs of the reconstruction theorem and the multilevel Schauder estimate for singular modelled distributions. As an application of them, we construct the local-in-time…

Probability · Mathematics 2025-03-11 Masato Hoshino , Ryoji Takano

It is well known that the category of quasi-coherent sheaves on a gerbe banded by a diagonalizable group decomposes according to the characters of the group. We establish the corresponding decomposition of the unbounded derived category of…

Algebraic Geometry · Mathematics 2019-02-20 Daniel Bergh , Olaf M. Schnürer

We introduce a unified framework based on bi-level optimization schemes to deal with parameter learning in the context of image processing. The goal is to identify the optimal regularizer within a family depending on a parameter in a…

Analysis of PDEs · Mathematics 2022-09-15 Elisa Davoli , Rita Ferreira , Carolin Kreisbeck , Hidde Schönberger

Spectral clustering and diffusion maps are celebrated dimensionality reduction algorithms built on eigen-elements related to the diffusive structure of the data. The core of these procedures is the approximation of a Laplacian through a…

Machine Learning · Statistics 2023-02-15 Loucas Pillaud-Vivien , Francis Bach

Can graded meshes yield more accurate numerical solution than uniform meshes? A time-dependent nonlocal diffusion problem with a weakly singular kernel is considered using collocation method. For its steady-state counterpart, under the…

Numerical Analysis · Mathematics 2024-02-01 Minghua Chen , Chao Min , Jiankang Shi , Jizeng Wang

We present an approach to model-based hierarchical clustering by formulating an objective function based on a Bayesian analysis. This model organizes the data into a cluster hierarchy while specifying a complex feature-set partitioning that…

Machine Learning · Computer Science 2013-01-18 Shivakumar Vaithyanathan , Byron E Dom

We study the structure of generalized Baumslag-Solitar groups from the point of view of their (usually non-unique) splittings as fundamental groups of graphs of infinite cyclic groups. We find and characterize certain decompositions of…

Group Theory · Mathematics 2016-09-13 Max Forester

We focus on topological equisingularity of families of holomorphic function germs with 1-dimensional critical set. We introduce the notion of equisingularity at the critical set and prove that any family which is equisingular at the…

Algebraic Geometry · Mathematics 2007-05-23 Javier Fernandez de Bobadilla

We study tangential families, i.e. systems of rays emanating tangentially from given curves. We classify, up to Left-Right equivalence, stable singularities of tangential family germs (under deformations among tangential families) and we…

Differential Geometry · Mathematics 2007-05-23 Gianmarco Capitanio