@article{1252,
abstract = {We study the homomorphism induced in homology by a closed correspondence between topological spaces, using projections from the graph of the correspondence to its domain and codomain. We provide assumptions under which the homomorphism induced by an outer approximation of a continuous map coincides with the homomorphism induced in homology by the map. In contrast to more classical results we do not require that the projection to the domain have acyclic preimages. Moreover, we show that it is possible to retrieve correct homological information from a correspondence even if some data is missing or perturbed. Finally, we describe an application to combinatorial maps that are either outer approximations of continuous maps or reconstructions of such maps from a finite set of data points.},
author = {Harker, Shaun and Kokubu, Hiroshi and Mischaikow, Konstantin and Pilarczyk, Pawel},
journal = {Proceedings of the American Mathematical Society},
number = {4},
pages = {1787 -- 1801},
publisher = {American Mathematical Society},
title = {{Inducing a map on homology from a correspondence}},
doi = {10.1090/proc/12812},
volume = {144},
year = {2016},
}
@article{1254,
abstract = {We use rigorous numerical techniques to compute a lower bound for the exponent of expansivity outside a neighborhood of the critical point for thousands of intervals of parameter values in the quadratic family. We first compute a radius of the critical neighborhood outside which the map is uniformly expanding. This radius is taken as small as possible, yet large enough for our numerical procedure to succeed in proving that the expansivity exponent outside this neighborhood is positive. Then, for each of the intervals, we compute a lower bound for this expansivity exponent, valid for all the parameters in that interval. We illustrate and study the distribution of the radii and the expansivity exponents. The results of our computations are mathematically rigorous. The source code of the software and the results of the computations are made publicly available at http://www.pawelpilarczyk.com/quadratic/.},
author = {Golmakani, Ali and Luzzatto, Stefano and Pilarczyk, Pawel},
journal = {Experimental Mathematics},
number = {2},
pages = {116 -- 124},
publisher = {Taylor and Francis},
title = {{Uniform expansivity outside a critical neighborhood in the quadratic family}},
doi = {10.1080/10586458.2015.1048011},
volume = {25},
year = {2016},
}
@article{1272,
abstract = {We study different means to extend offsetting based on skeletal structures beyond the well-known constant-radius and mitered offsets supported by Voronoi diagrams and straight skeletons, for which the orthogonal distance of offset elements to their respective input elements is constant and uniform over all input elements. Our main contribution is a new geometric structure, called variable-radius Voronoi diagram, which supports the computation of variable-radius offsets, i.e., offsets whose distance to the input is allowed to vary along the input. We discuss properties of this structure and sketch a prototype implementation that supports the computation of variable-radius offsets based on this new variant of Voronoi diagrams.},
author = {Held, Martin and Huber, Stefan and Palfrader, Peter},
journal = {Computer-Aided Design and Applications},
number = {5},
pages = {712 -- 721},
publisher = {Taylor and Francis},
title = {{Generalized offsetting of planar structures using skeletons}},
doi = {10.1080/16864360.2016.1150718},
volume = {13},
year = {2016},
}
@article{1289,
abstract = {Aiming at the automatic diagnosis of tumors using narrow band imaging (NBI) magnifying endoscopic (ME) images of the stomach, we combine methods from image processing, topology, geometry, and machine learning to classify patterns into three classes: oval, tubular and irregular. 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 and Kuvaev, Roman and Kashin, Sergey},
journal = {Pattern Recognition Letters},
number = {1},
pages = {13 -- 22},
publisher = {Elsevier},
title = {{The classification of endoscopy images with persistent homology}},
doi = {10.1016/j.patrec.2015.12.012},
volume = {83},
year = {2016},
}
@article{1292,
abstract = {We give explicit formulas and algorithms for the computation of the Thurstonâ€“Bennequin invariant of a nullhomologous Legendrian knot on a page of a contact open book and on Heegaard surfaces in convex position. Furthermore, we extend the results to rationally nullhomologous knots in arbitrary 3-manifolds.},
author = {Durst, Sebastian and Kegel, Marc and Klukas, Mirko D},
journal = {Acta Mathematica Hungarica},
number = {2},
pages = {441 -- 455},
publisher = {Springer},
title = {{Computing the Thurstonâ€“Bennequin invariant in open books}},
doi = {10.1007/s10474-016-0648-4},
volume = {150},
year = {2016},
}