@article{1578,
abstract = {We prove that the dual of the digital Voronoi diagram constructed by flooding the plane from the data points gives a geometrically and topologically correct dual triangulation. This provides the proof of correctness for recently developed GPU algorithms that outperform traditional CPU algorithms for constructing two-dimensional Delaunay triangulations.},
author = {Cao, Thanhtung and Edelsbrunner, Herbert and Tan, Tiowseng},
journal = {Computational Geometry},
number = {7},
pages = {507 -- 519},
publisher = {Elsevier},
title = {{Triangulations from topologically correct digital Voronoi diagrams}},
doi = {10.1016/j.comgeo.2015.04.001},
volume = {48},
year = {2015},
}
@article{1531,
abstract = {The Heat Kernel Signature (HKS) is a scalar quantity which is derived from the heat kernel of a given shape. Due to its robustness, isometry invariance, and multiscale nature, it has been successfully applied in many geometric applications. From a more general point of view, the HKS can be considered as a descriptor of the metric of a Riemannian manifold. Given a symmetric positive definite tensor field we may interpret it as the metric of some Riemannian manifold and thereby apply the HKS to visualize and analyze the given tensor data. In this paper, we propose a generalization of this approach that enables the treatment of indefinite tensor fields, like the stress tensor, by interpreting them as a generator of a positive definite tensor field. To investigate the usefulness of this approach we consider the stress tensor from the two-point-load model example and from a mechanical work piece.},
author = {Zobel, Valentin and Jan Reininghaus and Hotz, Ingrid},
journal = {Mathematics and Visualization},
pages = {257 -- 267},
publisher = {Springer},
title = {{Visualizing symmetric indefinite 2D tensor fields using The Heat Kernel Signature}},
doi = {10.1007/978-3-319-15090-1_13},
volume = {40},
year = {2015},
}
@article{1555,
abstract = {We show that incorporating spatial dispersal of individuals into a simple vaccination epidemic model may give rise to a model that exhibits rich dynamical behavior. Using an SIVS (susceptible-infected-vaccinated-susceptible) model as a basis, we describe the spread of an infectious disease in a population split into two regions. In each subpopulation, both forward and backward bifurcations can occur. This implies that for disconnected regions the two-patch system may admit several steady states. We consider traveling between the regions and investigate the impact of spatial dispersal of individuals on the model dynamics. We establish conditions for the existence of multiple nontrivial steady states in the system, and we study the structure of the equilibria. The mathematical analysis reveals an unusually rich dynamical behavior, not normally found in the simple epidemic models. In addition to the disease-free equilibrium, eight endemic equilibria emerge from backward transcritical and saddle-node bifurcation points, forming an interesting bifurcation diagram. Stability of steady states, their bifurcations, and the global dynamics are investigated with analytical tools, numerical simulations, and rigorous set-oriented numerical computations.},
author = {Knipl, Diána and Pilarczyk, Pawel and Röst, Gergely},
journal = {SIAM Journal on Applied Dynamical Systems},
number = {2},
pages = {980 -- 1017},
publisher = {Society for Industrial and Applied Mathematics },
title = {{Rich bifurcation structure in a two patch vaccination model}},
doi = {10.1137/140993934},
volume = {14},
year = {2015},
}
@inproceedings{1567,
abstract = {My personal journey to the fascinating world of geometric forms started more than 30 years ago with the invention of alpha shapes in the plane. It took about 10 years before we generalized the concept to higher dimensions, we produced working software with a graphics interface for the three-dimensional case. At the same time, we added homology to the computations. Needless to say that this foreshadowed the inception of persistent homology, because it suggested the study of filtrations to capture the scale of a shape or data set. Importantly, this method has fast algorithms. The arguably most useful result on persistent homology is the stability of its diagrams under perturbations.},
author = {Edelsbrunner, Herbert},
location = {Los Angeles, CA, United States},
publisher = {Springer},
title = {{Shape, homology, persistence, and stability}},
volume = {9411},
year = {2015},
}
@article{1682,
abstract = {We study the problem of robust satisfiability of systems of nonlinear equations, namely, whether for a given continuous function f:K→ ℝn on a finite simplicial complex K and α > 0, it holds that each function g: K → ℝn such that ||g - f || ∞ < α, has a root in K. Via a reduction to the extension problem of maps into a sphere, we particularly show that this problem is decidable in polynomial time for every fixed n, assuming dimK ≤ 2n - 3. This is a substantial extension of previous computational applications of topological degree and related concepts in numerical and interval analysis. Via a reverse reduction, we prove that the problem is undecidable when dim K > 2n - 2, where the threshold comes from the stable range in homotopy theory. For the lucidity of our exposition, we focus on the setting when f is simplexwise linear. Such functions can approximate general continuous functions, and thus we get approximation schemes and undecidability of the robust satisfiability in other possible settings.},
author = {Franek, Peter and Krcál, Marek},
journal = {Journal of the ACM},
number = {4},
publisher = {ACM},
title = {{Robust satisfiability of systems of equations}},
doi = {10.1145/2751524},
volume = {62},
year = {2015},
}
@inproceedings{1424,
abstract = {We consider the problem of statistical computations with persistence diagrams, a summary representation of topological features in data. These diagrams encode persistent homology, a widely used invariant in topological data analysis. While several avenues towards a statistical treatment of the diagrams have been explored recently, we follow an alternative route that is motivated by the success of methods based on the embedding of probability measures into reproducing kernel Hilbert spaces. In fact, a positive definite kernel on persistence diagrams has recently been proposed, connecting persistent homology to popular kernel-based learning techniques such as support vector machines. However, important properties of that kernel enabling a principled use in the context of probability measure embeddings remain to be explored. Our contribution is to close this gap by proving universality of a variant of the original kernel, and to demonstrate its effective use in twosample hypothesis testing on synthetic as well as real-world data.},
author = {Kwitt, Roland and Huber, Stefan and Niethammer, Marc and Lin, Weili and Bauer, Ulrich},
location = {Montreal, Canada},
pages = {3070 -- 3078},
publisher = {Neural Information Processing Systems},
title = {{Statistical topological data analysis-A kernel perspective}},
volume = {28},
year = {2015},
}
@article{1563,
abstract = {For a given self-map $f$ of $M$, a closed smooth connected and simply-connected manifold of dimension $m\geq 4$, we provide an algorithm for estimating the values of the topological invariant $D^m_r[f]$, which equals the minimal number of $r$-periodic points in the smooth homotopy class of $f$. Our results are based on the combinatorial scheme for computing $D^m_r[f]$ introduced by G. Graff and J. Jezierski [J. Fixed Point Theory Appl. 13 (2013), 63-84]. An open-source implementation of the algorithm programmed in C++ is publicly available at {\tt http://www.pawelpilarczyk.com/combtop/}.},
author = {Graff, Grzegorz and Pilarczyk, Pawel},
journal = {Topological Methods in Nonlinear Analysis},
number = {1},
pages = {273 -- 286},
publisher = {Juliusz Schauder Center for Nonlinear Studies},
title = {{An algorithmic approach to estimating the minimal number of periodic points for smooth self-maps of simply-connected manifolds}},
doi = {10.12775/TMNA.2015.014},
volume = {45},
year = {2015},
}
@inproceedings{1568,
abstract = {Aiming at the automatic diagnosis of tumors from narrow band imaging (NBI) magnifying endoscopy (ME) images of the stomach, we combine methods from image processing, computational topology, and machine learning to classify patterns into normal, tubular, vessel. Training the algorithm on a small number of images of each type, we achieve a high rate of correct classifications. The analysis of the learning algorithm reveals that a handful of geometric and topological features are responsible for the overwhelming majority of decisions.},
author = {Dunaeva, Olga and Edelsbrunner, Herbert and Lukyanov, Anton and Machin, Michael and Malkova, Daria},
booktitle = {Proceedings - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing},
location = {Timisoara, Romania},
pages = {7034731},
publisher = {IEEE},
title = {{The classification of endoscopy images with persistent homology}},
doi = {10.1109/SYNASC.2014.81},
year = {2015},
}
@article{1582,
abstract = {We investigate weighted straight skeletons from a geometric, graph-theoretical, and combinatorial point of view. We start with a thorough definition and shed light on some ambiguity issues in the procedural definition. We investigate the geometry, combinatorics, and topology of faces and the roof model, and we discuss in which cases a weighted straight skeleton is connected. Finally, we show that the weighted straight skeleton of even a simple polygon may be non-planar and may contain cycles, and we discuss under which restrictions on the weights and/or the input polygon the weighted straight skeleton still behaves similar to its unweighted counterpart. In particular, we obtain a non-procedural description and a linear-time construction algorithm for the straight skeleton of strictly convex polygons with arbitrary weights.},
author = {Biedl, Therese and Held, Martin and Huber, Stefan and Kaaser, Dominik and Palfrader, Peter},
journal = {Computational Geometry: Theory and Applications},
number = {2},
pages = {120 -- 133},
publisher = {Elsevier},
title = {{Weighted straight skeletons in the plane}},
doi = {10.1016/j.comgeo.2014.08.006},
volume = {48},
year = {2015},
}
@article{1828,
abstract = {We construct a non-linear Markov process connected with a biological model of a bacterial genome recombination. The description of invariant measures of this process gives us the solution of one problem in elementary probability theory.},
author = {Akopyan, Arseniy and Pirogov, Sergey and Rybko, Aleksandr},
journal = {Journal of Statistical Physics},
number = {1},
pages = {163 -- 167},
publisher = {Springer},
title = {{ Invariant measures of genetic recombination process}},
doi = {10.1007/s10955-015-1238-5},
volume = {160},
year = {2015},
}