3 citations · 15 across the 27 of their papers we have counts for
5 papers · 1 filter
On the Geometry and Optimization of Polynomial Convolutional Networks
Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn
We study convolutional neural networks with monomial activation functions. Specifically, we prove that their parameterization map is regular and is an isomorphism almost everywhere…
Relative Representations: Topological and Geometric Perspectives
Alejandro García-Castellanos, Giovanni Luca Marchetti, Danica Kragic +1
Relative representations are an established approach to zero-shot model stitching, consisting of a non-trainable transformation of the latent space of a deep neural network. Based…
HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees
Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti +2
We propose HyperSteiner -- an efficient heuristic algorithm for computing Steiner minimal trees in the hyperbolic space. HyperSteiner extends the Euclidean Smith-Lee-Liebman algori…
Geometry of Lightning Self-Attention: Identifiability and Dimension
Nathan W. Henry, Giovanni Luca Marchetti, Kathlén Kohn
We consider function spaces defined by self-attention networks without normalization, and theoretically analyze their geometry. Since these networks are polynomial, we rely on tool…
Hyperbolic Delaunay Geometric Alignment
Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii +4
Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resu…