2 papers
cs.LG2025
Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
Adrian Arnaiz-Rodriguez, Federico Errica
After a renaissance phase in which researchers revisited the message-passing paradigm through the lens of deep learning, the graph machine learning community shifted its attention…
cs.LG2024
The Disparate Benefits of Deep Ensembles
Kajetan Schweighofer, Adrian Arnaiz-Rodriguez, Sepp Hochreiter +1
Ensembles of Deep Neural Networks, Deep Ensembles, are widely used as a simple way to boost predictive performance. However, their impact on algorithmic fairness is not well unders…