2 papers
cs.LG2024
CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs
Davide Buffelli, Farzin Soleymani, Bastian Rieck
Graph neural networks have become the default choice by practitioners for graph learning tasks such as graph classification and node classification. Nevertheless, popular graph neu…
cs.CV2021
Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images
Farzin Soleymani, Mohammad Eslami, Tobias Elze +2
We propose a Deep Variational Clustering (DVC) framework for unsupervised representation learning and clustering of large-scale medical images. DVC simultaneously learns the multiv…