David Eklund

activity

20092020

collaborators

5 papers

cs.LG2020

Variational Autoencoders with Riemannian Brownian Motion Priors

Dimitris Kalatzis, David Eklund, Georgios Arvanitidis +1

Variational Autoencoders (VAEs) represent the given data in a low-dimensional latent space, which is generally assumed to be Euclidean. This assumption naturally leads to the commo…

cs.LG2019

Expected path length on random manifolds

David Eklund, Søren Hauberg

Manifold learning seeks a low dimensional representation that faithfully captures the essence of data. Current methods can successfully learn such representations, but do not provi…

math.AG2019

The bottleneck degree of algebraic varieties

Sandra Di Rocco, David Eklund, Madeleine Weinstein

A bottleneck of a smooth algebraic variety $X \subset C^{n}$ is a pair of distinct points $(x, y) \in X$ such that the Euclidean normal spaces at $x$ and $y$ contain the line…

math.AG2017

Numerical Polar calculus and cohomology of line bundles

Sandra Di Rocco, David Eklund, Chris Peterson

Let $L_{1}, \dots, L_{s}$ be line bundles on a smooth variety $X \subset P^{r}$ and let $D_{1}, \dots, D_{s}$ be divisors on $X$ such that $D_{i}$ represents $L_{i}$ . We give a probabilistic…

math.AG2009

Chern Numbers of Smooth Varieties via Homotopy Continuation and Intersection Theory

Sandra Di Rocco, David Eklund, Chris Petersen +1

Homotopy continuation provides a numerical tool for computing the equivalence of a smooth variety in an intersection product. Intersection theory provides a theoretical tool for re…