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This paper is devoted to the specific class of pseudoconformal mappings of quaternion and octonion variables. Normal families of functions are defined and investigated. Four criteria of a family being normal are proven. Then groups of…

Differential Geometry · Mathematics 2018-12-18 S. V. Ludkovsky

We determine the Riemannian manifolds for which the group of exact volume preserving diffeomorphisms is a totally geodesic subgroup of the group of volume preserving diffeomorphisms, considering right invariant $L^2$-metrics. The same is…

Differential Geometry · Mathematics 2009-11-07 Stefan Haller , Josef Teichmann , Cornelia Vizman

To every closed subset $X$ of a symplectic manifold $(M,\omega)$ we associate a natural group of Hamiltonian diffeomorphisms $Ham(X,\omega)$. We equip this group with a semi-norm $\Vert\cdot\Vert^{X,\omega}$, generalizing the Hofer norm. We…

Symplectic Geometry · Mathematics 2011-02-25 Jan Swoboda , Fabian Ziltener

We establish the equivalence between the family of closed uniformly regular Riemannian manifolds and the class of complete manifolds with bounded geometry.

Differential Geometry · Mathematics 2016-04-08 Marcelo Disconzi , Yuanzhen Shao , Gieri Simonett

These notes on Riemannian geometry use the bases bundle and frame bundle, as in Geometry of Manifolds, to express the geometric structures. It has more problems and omits the background material. It starts with the definition of Riemannian…

Differential Geometry · Mathematics 2013-07-30 Richard L. Bishop

Riemannian neural networks, which extend deep learning techniques to Riemannian spaces, have gained significant attention in machine learning. To better classify the manifold-valued features, researchers have started extending Euclidean…

Machine Learning · Computer Science 2024-10-03 Ziheng Chen , Yue Song , Rui Wang , Xiaojun Wu , Nicu Sebe

We consider an inference on the eigenvalues of the covariance matrix of a multivariate normal distribution. The family of multivariate normal distributions with a fixed mean is seen as a Riemannian manifold with Fisher information metric.…

Statistics Theory · Mathematics 2018-10-12 Yo Sheena

For a compact $(2n+1)$-dimensional smooth manifold, let $\mu_M : B Diff_\partial (D^{2n+1}) \to B Diff (M)$ be the map that is defined by extending diffeomorphisms on an embedded disc by the identity. By a classical result of Farrell and…

Algebraic Topology · Mathematics 2023-08-02 Johannes Ebert

H. Hertz called any manifold M with a given nonintegrable distribution {\it nonholonomic}. Vershik and Gershkovich stated and R. Montgomery proved that the space of germs of any nonholonomic distribution on M with an open and dense orbit of…

Representation Theory · Mathematics 2007-05-23 Pavel Grozman , Dimitry Leites , Irina Shchepochkina

We define new Riemannian structures on 7-manifolds by a differential form of mixed degree which is the critical point of a (possibly constrained) variational problem over a fixed cohomology class. The unconstrained critical points…

Differential Geometry · Mathematics 2009-11-10 Frederik Witt

A 4-dimensional Riemannian manifold equipped with an endomorphism of the tangent bundle, whose fourth power is the identity, is considered. The matrix of this structure in some basis is circulant and the structure acts as an isometry with…

Differential Geometry · Mathematics 2021-06-25 Iva Dokuzova , Dimitar Razpopov , Mancho Manev

A generalized Stiefel manifold is the manifold of orthonormal frames in a vector space with a non-degenerated bilinear or hermitian form. In this article, the Isometry group of the generalized Stiefel manifolds are computed at least up to…

Differential Geometry · Mathematics 2019-05-22 Manuel Sedano-Mendoza

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

In this note, we describe the geometry of the quaternionic Heisenberg groups from a Riemannian viewpoint. We show, in all dimensions, that they carry an almost $3$-contact metric structure which allows us to define the metric connection…

Differential Geometry · Mathematics 2015-10-28 Ilka Agricola , Ana Cristina Ferreira , Reinier Storm

We define intrinsic torsion in generalised geometry and use it to introduce a new notion of generalised special holonomy. We then consider generic warped supersymmetric flux compactifications of M theory and Type II of the form…

High Energy Physics - Theory · Physics 2016-07-07 André Coimbra , Charles Strickland-Constable , Daniel Waldram

In this paper, we prove normality criteria for families of meromorphic functions involving sharing of a holomorphic function by a certain class of differential polynomials. Results in this paper extends the works of different authors…

Complex Variables · Mathematics 2015-04-01 Virender Singh , Kuldeep Singh Charak

A spectral sequence calculating the homology groups of some spaces of maps equivariant under compact group actions is described. For the main example, we calculate the rational homology groups of spaces of even and odd maps $S^m \to S^M$,…

Algebraic Topology · Mathematics 2021-07-01 Victor Vassiliev

Orthogonal polynomials with respect to the hypergeometric distribution on lattices in polyhedral domains in ${\mathbb R}^d$, which include hexagons in ${\mathbb R}^2$ and truncated tetrahedrons in ${\mathbb R}^3$, are defined and studied.…

Classical Analysis and ODEs · Mathematics 2020-02-13 Plamen Iliev , Yuan Xu

Motivated by a paper of Zirnbauer, we develop a theory of Riemannian supermanifolds up to a definition of Riemannian symmetric superspaces. Various fundamental concepts needed for the study of these spaces both from the Riemannian and the…

Differential Geometry · Mathematics 2009-08-12 Oliver Goertsches

The generalized partially linear models on Riemannian manifolds are introduced. These models, like ordinary generalized linear models, are a generalization of partially linear models on Riemannian manifolds that allow for response variables…

Methodology · Statistics 2018-03-09 Amelia Simó , M. Victoria Ibáñez , Irene Epifanio , Vicent Gimeno
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