13 citations · 24 across the 6 of their papers we have counts for
6 papers
The Flood Complex: Large-Scale Persistent Homology on Millions of Points
Florian Graf, Paolo Pellizzoni, Martin Uray +2
We consider the problem of computing persistent homology (PH) for large-scale Euclidean point cloud data, aimed at downstream machine learning tasks, where the exponential growth o…
Endowing Protein Language Models with Structural Knowledge
Dexiong Chen, Philip Hartout, Paolo Pellizzoni +2
Understanding the relationships between protein sequence, structure and function is a long-standing biological challenge with manifold implications from drug design to our understa…
Fisher Information Embedding for Node and Graph Learning
Dexiong Chen, Paolo Pellizzoni, Karsten Borgwardt
Attention-based graph neural networks (GNNs), such as graph attention networks (GATs), have become popular neural architectures for processing graph-structured data and learning no…
Fully dynamic clustering and diversity maximization in doubling metrics
Paolo Pellizzoni, Andrea Pietracaprina, Geppino Pucci
We present approximation algorithms for some variants of center-based clustering and related problems in the fully dynamic setting, where the pointset evolves through an arbitrary…
Dimensionality Reduction on Complex Vector Spaces for Euclidean Distance with Dynamic Weights
Simone Moretti, Paolo Pellizzoni, Francesco Silvestri
The weighted Euclidean norm of a vector with weights is the Euclidean norm where the contribution of each dimension is scaled by a…
k-Center Clustering with Outliers in Sliding Windows
Paolo Pellizzoni, Andrea Pietracaprina, Geppino Pucci
Metric -center clustering is a fundamental unsupervised learning primitive. Although widely used, this primitive is heavily affected by noise in the data, so that a more sensibl…