4 papers · 1 filter
GEM-FI: Gated Evidential Mixtures with Fisher Modulation
Marco Mustafa Mohammed, Fatemeh Daneshfar, Pietro Liò
Evidential Deep Learning (EDL) enables single-pass uncertainty estimation by predicting Dirichlet evidence, but it can remain overconfident and poorly calibrated, and it often fail…
How Smoothing is N-simplicial Attention?
Alexandre Dussolle, Pietro Liò
Going from pure Multilayer Perceptron (MLP) to a learnable graph message-passing mechanism at each layer has been foundational to state-of-the-art results, despite the computationa…
On the Sheafification of Higher-Order Message Passing
Jacob Hume, Pietro Liò
Recent work in Topological Deep Learning (TDL) seeks to generalize graph learning's preeminent paradigm to more complex relational structures: simplicial comple…
E(n) Equivariant Message Passing Cellular Networks
Veljko Kovač, Erik J. Bekkers, Pietro Liò +1
This paper introduces E(n) Equivariant Message Passing Cellular Networks (EMPCNs), an extension of E(n) Equivariant Graph Neural Networks to CW-complexes. Our approach addresses tw…