Horizontal points of smooth submanifolds in stratified groups play the role of singular points with respect to the Carnot-Carathe'odory distance. When we consider hypersurfaces, they coincide with the well known characteristic points. In two step groups, we obtain pointwise estimates for the Riemannian surface measure …
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19 results for “Carathéodory pseudo-distance”
The subject of these Notes is the new proof, proposed in [F. H{é}lein, In{é}galit{é} isop{é}rim{é}trique et calibrations, Annales de l'Institut Fourier 44, 4 (1994), 1211-1218] of the classical isoperimetric inequality in the plane. This proof is far from being the first one, but its interest is that it uses essentiall…
Different distances on symmetrical domains in complex space.
problem Comparing distances on specific complex domains.
method Examined Carathéodory pseudo-distance and Kähler-Einstein metric distances.
result Found the distances differ on certain complex domains.
The concept of natural pseudo-distance has proven to be a powerful tool for measuring the dissimilarity between topological spaces endowed with continuous real-valued functions. Roughly speaking, the natural pseudo-distance is defined as the infimum of the change of the functions' values, when moving from one space to …
Here, a non-linear analysis method is applied rather than classical one to study projective changes of Finsler metrics. More intuitively, a projectively invariant pseudo-distance is introduced and characterized with respect to the Ricci tensor and its covariant derivatives.
A projective parameter of a geodesic on a Finsler space is defined to be solution of a certain ODE. Using projective parameter and Funk metric, one can construct a projectively invariant intrinsic pseudo-distance on a Finsler space. In the present work, solutions of the projective parameter's ODE are characterized with…
Complete Finsler spaces with negative Ricci curvature are reversible.
problem Characterizing Finsler spaces with constant negative Ricci curvature.
method Utilizing projectively invariant pseudo-distance and Schwarzian derivative.
result Every connected complete Finsler space with constant negative Ricci scalar is reversible.
Here, a non-linear analysis method is applied rather than classical one to study projective Finsler geometry. More intuitively, by means of an inequality on Ricci-Finsler curvature, a projectively invariant pseudo-distance is introduced and an analogous of Schwarz' lemma in Finsler geometry is proved. Next, the Schwarz…
Sub-Riemannian Snakes on the Projective Line Bundle with Applications to Segmentation of SEM Imagesmath.DG
A new snake model improves segmentation of SEM images.
problem Efficiently segmenting overlapping electronic structures in SEM images.
method Geodesic tracking on projective line bundle with a geometric criterion for switching between fast spatial snakes and minimizing geodesics.
result Improved robust and automatic segmentation of overlapping electronic structures in SEM images.
End-to-end approach learns pseudo-distance for verifying example sets.
problem Verifying example sets from same or different classes.
method Jointly trains parametric pseudo-distance with encoder.
result End-to-end approach outperforms simple scorers and classifiers.
Paper develops a continuous-time framework for financial markets without stochastic calculus.
problem Developing continuous-time financial models without stochastic calculus.
method A general framework using conditional topologies and pseudo-distance topologies.
result No-arbitrage conditions hold in continuous time if and only if they hold in discrete time.
We study space-like self-shrinkers of dimension in pseudo-Euclidean space $\ir{m+n}_m$with index . We derive drift Laplacian of the basic geometric quantities and obtain their volume estimates in pseudo-distance function. Finally, we prove a rigidity results under minor growth conditions interms of the mean curv…
We define a concept which we call multiplicity. First, multiplicity of a morphism is defined. Then the multiplicity of an object over another object is defined to be the minimum of the multiplicities of all morphisms from one to another. Based on this multiplicity, we define a pseudo distance on the class of objects. W…
I introduce a family of closeness functions between causal Lorentzian geometries of finite volume and arbitrary underlying topology. When points are randomly scattered in a Lorentzian manifold, with uniform density according to the volume element, some information on the topology and metric is encoded in the partial or…
New divergence defined in Information Geometry mimics Riemannian geodesics.
problem Defining a canonical divergence in Information Geometry.
method Extending Riemannian geodesics to Information Geometry, defining new divergence.
result New divergence recovers dual structures and coincides with existing ones.
SRNF framework extends surface distance to Lipschitz surfaces.
problem Defining a distance metric for unparametrized surfaces.
method Square Root Normal Fields (SRNF) and Wasserstein Fisher Rao (WFR) metric.
result SRNF distance on Lipschitz surfaces is equivalent to WFR metric.
This paper generalizes Sinkhorn algorithm for unbalanced optimal transport.
problem Handling distributions with different total mass and robustness to outliers.
method Alternates between standard Sinkhorn updates and pointwise application of a contractive function.
result Defines Sinkhorn divergences that are differentiable, positive, definite, convex, and robust.
A new method for comparing measures in different spaces using flow alignment.
problem Comparing probability measures in different metric spaces with computational efficiency.
method Flow-based Alignment (\FlowAlign) and Depth-based Alignment (\DepthAlign) using tree structures.
result Flow-based Alignment and Depth-based Alignment are pseudo-distances and scalable for large-scale applications.
New optimization technique for aligning points to lines, improving existing algorithms.
problem Minimizing distances between points and lines with given constraints.
method Combining techniques from computational geometry, combinatorics, and convex optimization.
result First constant-factor approximation algorithms for Points-to-Lines alignment with polynomial running time.