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We propose a novel ECGAN for the challenging semantic image synthesis task. Although considerable improvement has been achieved, the quality of synthesized images is far from satisfactory due to three largely unresolved challenges. 1) The…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Hao Tang , Xiaojuan Qi , Guolei Sun , Dan Xu , Nicu Sebe , Radu Timofte , Luc Van Gool

Inequalities for norms of different versions of the geometric mean of two positive definite matrices are presented.

Functional Analysis · Mathematics 2015-02-17 Rajendra Bhatia , Priyanka Grover

The linearizability of differential equations was first considered by Lie for scalar second order semi-linear ordinary differential equations. Since then there has been considerable work done on the algebraic classification of linearizable…

Classical Analysis and ODEs · Mathematics 2008-04-25 Asghar Qadir

The notion of "super convex spaces" generalizes the idea of convex spaces by replacing finite affine sums with countable affine sums. Using this notion permits a very elegant approach for analysis of the Giry monad on standard measurable…

Category Theory · Mathematics 2022-08-09 Kirk Sturtz

Many deep generative models are defined as a push-forward of a Gaussian measure by a continuous generator, such as Generative Adversarial Networks (GANs) or Variational Auto-Encoders (VAEs). This work explores the latent space of such deep…

Machine Learning · Computer Science 2023-05-16 Thibaut Issenhuth , Ugo Tanielian , Jérémie Mary , David Picard

In this paper, we study metric completions of triangulated categories in a representation-theoretic context. We provide a concrete description of completions of bounded derived categories of hereditary finite dimensional algebras of finite…

Representation Theory · Mathematics 2026-01-22 Cyril Matoušek

In this article, we analyze three classes of time-reversal of a Markov process with Gaussian noise on a manifold. We first unveil a commutativity constraint for the most general of these time-reversals to be well defined. Then we give a…

Statistical Mechanics · Physics 2024-08-09 Jérémy O'Byrne , Michael E. Cates

We define a regularized size-shape distortion (quality) measure for curved high-order elements on a Riemannian space. To this end, we measure the deviation of a given element, straight-sided or curved, from the stretching, alignment, and…

Computational Engineering, Finance, and Science · Computer Science 2024-03-21 Guillermo Aparicio-Estrems , Abel Gargallo-Peiró , Xevi Roca

A geometric graph is a combinatorial graph, endowed with a geometry that is inherited from its embedding in a Euclidean space. Formulation of a meaningful measure of (dis-)similarity in both the combinatorial and geometric structures of two…

Computational Geometry · Computer Science 2022-09-27 Sushovan Majhi , Carola Wenk

Noticing that all of the 19th, 20th and 21st centuries treatments of trigonometry surveyed in this article are conceptually or logically defective, it is required to seek a conceptually sound and logically correct foundations of the…

History and Overview · Mathematics 2026-01-29 Mohamed A. Amer

Generalized equations are problems emerging in contexts of modern variational analysis as an adequate formalism to treat such issues as constraint systems, optimality and equilibrium conditions, variational inequalities, differential…

Optimization and Control · Mathematics 2018-12-06 A Uderzo

The convex and metric structures underlying probabilistic physical theories are generally described in terms of base normed vector spaces. According to a recent proposal, the purely geometrical features of these spaces are appropriately…

Mathematical Physics · Physics 2011-01-04 P. Busch

An inductive mean is a mean defined as a limit of a convergence sequence of other means. Historically, this notion of inductive means obtained as limits of sequences was pioneered independently by Lagrange and Gauss for defining the…

Information Theory · Computer Science 2024-10-22 Frank Nielsen

Uniform measures have played a fundamental role in geometric measure theory since they naturally appear as tangent objects. For instance, they were essential in the groundbreaking work of Preiss on the rectifiability of Radon measures.…

Metric Geometry · Mathematics 2018-03-26 A. Dali Nimer

For a large class of statistical systems a geometric mean value of the observables is constrained. These observables are characterized by a power-law statistical distribution.

Statistical Mechanics · Physics 2007-05-23 A. Rostovtsev

A natural way of handling imbalanced data is to attempt to equalise the class frequencies and train the classifier of choice on balanced data. For two-class imbalanced problems, the classification success is typically measured by the…

Computer Vision and Pattern Recognition · Computer Science 2018-04-20 Ludmila I. Kuncheva , Álvar Arnaiz-González , José-Francisco Díez-Pastor , Iain A. D. Gunn

In recent years, in an effort to promote fairness in the election process, a wide variety of techniques and metrics have been proposed to determine whether a map is a partisan gerrymander. The most accessible measures, requiring easily…

Physics and Society · Physics 2025-08-11 Thomas Ratliff , Stephanie Somersille , Ellen Veomett

Three-way dissimilarities are a generalization of (two-way) dissimilarities which can be used to indicate the lack of homogeneity or resemblance between any three objects. Such maps have applications in cluster analysis, and have been used…

Combinatorics · Mathematics 2017-10-19 Katharina T. Huber , Vincent Moulton , Guillaume E. Scholz

In the approximate integration some inequalities between the quadratures and the integrals approximated by them are called \emph{extremalities}. On the other hand, the set of all quadratures is convex. We are trying to find possible…

Classical Analysis and ODEs · Mathematics 2014-11-24 Teresa Rajba , Szymon Wasowicz

We propose an improved estimator for the multi-task averaging problem, whose goal is the joint estimation of the means of multiple distributions using separate, independent data sets. The naive approach is to take the empirical mean of each…

Machine Learning · Statistics 2020-11-16 Hannah Marienwald , Jean-Baptiste Fermanian , Gilles Blanchard