Detecting the dimension of a hidden manifold from a point sample has become an important problem in the current data-driven era. Indeed, estimating the shape dimension is often the first step in studying the processes or phenomena associated to the data. Among the many dimension detection algorithms proposed in various fields, a few can provide theoretical guarantee on the correctness of the es...

Given a set of points that sample a shape, the Rips complex of the points is often used to provide an approximation of the shape easily-computed. It has been proved that the Rips complex captures the homotopy type of the shape assuming the vertices of the complex meet some mild sampling conditions. Unfortunately, the Rips complex is generally high-dimensional. To remedy this problem, it is temp...

Automatic evaluation of the goodness Generative Adversarial Networks (GANs) has been a challenge for field machine learning. In this work, we propose distance complementary to existing measures: Topology Distance (TD), main idea behind which is compare geometric and topological features latent manifold real data with those generated data. More specifically, build Vietoris-Rips complex on image ...

Matchbox manifolds are foliated spaces whose transversal spaces are totally disconnected. In this work, we show that the local dynamics of a certain class of minimal matchbox manifolds classify their total space, up to homeomorphism. A key point is the use Alexandroff’s notion of a Y –like continuum, where Y is an aspherical closed manifold which satisfies the Borel Conjecture. In particular, w...

valuations on a topological space X are functions that map open sets to 0, 1, or one value in between. We deene a space of abstract valuations which for a continuous dcpo X is homeomorphic to the Plotkin power domain of X, and for a Hausdorr space X yields the Vietoris hyperspace of X. Thus we obtain a novel concrete representation of the Plotkin power domain. This representation is more simila...

In this work we investigate the parallel computation of homology using the Mayer-Vietoris principle. We present a two stage approach for parallelizing persistence. In the first stage, we produce a cover of the input cell complex by overlapping subspaces. In the second stage, we use this cover to build the Mayer-Vietoris blowup complex, a topological space, which organizes the various subspaces ...